Relationship between NAFLD and coronary artery disease: A Mendelian randomization study

BACKGROUND & AIMS: There is an ongoing debate on whether non-alcoholic fatty liver disease (NAFLD) is an active contributor or an innocent bystander in the pathogenesis of coronary artery disease (CAD). The aim of the present study was to assess the causal relationship between NAFLD and CAD. APPROACH & RESULTS: We performed two-sample Mendelian randomization (MR) analyses using summary-level data to assess the association between genetically predicted NAFLD (i.e. chronically-elevated serum alanine aminotransferase levels [cALT], imaging-based and biopsy-confirmed NAFLD) and risk of CAD. Analyses were repeated after exclusion of NAFLD susceptibility genes that are associated with impaired VLDL secretion. Inverse-variance weighted (IVW) MR analyses showed a statistically significant association between genetically predicted cALT and risk of CAD (odds ratio [OR]:1.116, 95% confidence interval [CI]:1.039,1.199), but not for the other NAFLD-related traits (OR:1.046, 95%CI:0.764,1.433 and OR:1.014, 95%CI:0.968,1.062 for imaging-based and biopsy-confirmed NAFLD, respectively). MR Egger regression revealed a statistically significant intercept, indicative of directional pleiotropy, for all traits. Repeat analyses after exclusion of genes associated with impaired VLDL secretion, showed consistent associations between genetically predicted NAFLD and CAD for all traits, i.e. cALT (OR:1.203, 95%CI:1.113,1.300), imaging-based (OR:2.149, 95%CI:1.276,3.620) and biopsy-confirmed NAFLD (OR:1.113, 95%CI:1.041,1.189), which persisted when more stringent biopsy-confirmed NAFLD criteria were used (OR:1.154, 95%CI:1.043,1.278) or when more stringent MR methods were applied. MR Egger regression did not show a statistically significant intercept. CONCLUSION: The two-sample MR analyses showed a robust association between genetically predicted NAFLD and CAD after exclusion of genetic variants that are implicated in impaired VLDL secretion

Spatiotemporal Dynamics of the Human Critical Area (HCA) in the “Three Water Lines” Region of Northwest China and the Impact of Socioeconomic Factors between 2000 and 2020

The Human Critical Area (HCA) is an area that characterizes the surface landscape created by human beings in the Anthropocene. Based on the signatures left by major human activities over the Earth′s surface, this research demarcates an arid inland region of Northwest China, the “Three Water Lines”, into four HCA types: Agricultural Area, Built-up Area, Ecological Area, and Bare Area. This paper explores the HCA′s distribution and changes in the “Three Water Lines” region between 2000 and 2020 with land use/cover data, as well as the impact of socioeconomic factors on the HCA dynamics with statistics sourcing from authoritative yearbooks. To achieve this, the Land Use Transition Matrix is used to investigate the changes in area and distribution, while binary linear regression and stepwise multiple linear regression are applied to examine the single and joint effects of the socioeconomic factors. The main findings are as follows: (i) The four HCA types are distinguished quantitatively and by their distribution patterns. Ecological Area and Bare Area cover most (more than 90% in total) of the territory with extensive and continuous distribution. Agricultural Area is mainly found on the eastern and western parts of the region, with flat terrain, abundant water resources, and moderate temperatures. Built-up Area is the most concentrated but has an unbalanced distribution and the lowest quantity. (ii) Despite some discernible spatial and quantity changes at regional and county levels between 2000 and 2020, the general characteristics in HCA’s structure and distribution pattern have mainly remained consistent. (iii) Transitions between HCA types occur constantly, and the primary source type of the transitions differs from one another. Ecological Area and Bare Area form the sources of the most evident transitions. (iv) Agricultural Area and Built-up Area are more prone influence from some socioeconomic dynamics. By contrast, there is no evidence that socioeconomic factors directly affect Bare Area. As the first empirical study of the newly conceived concept, Human Critical Area, this paper sheds light on the renovation of geographic traditions of studying the evolution of the human-environment system through the lens of human activities-driven landscape changes

Spatiotemporal Dynamics of the Human Critical Area (HCA) in the “Three Water Lines” Region of Northwest China and the Impact of Socioeconomic Factors between 2000 and 2020

The Human Critical Area (HCA) is an area that characterizes the surface landscape created by human beings in the Anthropocene. Based on the signatures left by major human activities over the Earth′s surface, this research demarcates an arid inland region of Northwest China, the “Three Water Lines”, into four HCA types: Agricultural Area, Built-up Area, Ecological Area, and Bare Area. This paper explores the HCA′s distribution and changes in the “Three Water Lines” region between 2000 and 2020 with land use/cover data, as well as the impact of socioeconomic factors on the HCA dynamics with statistics sourcing from authoritative yearbooks. To achieve this, the Land Use Transition Matrix is used to investigate the changes in area and distribution, while binary linear regression and stepwise multiple linear regression are applied to examine the single and joint effects of the socioeconomic factors. The main findings are as follows: (i) The four HCA types are distinguished quantitatively and by their distribution patterns. Ecological Area and Bare Area cover most (more than 90% in total) of the territory with extensive and continuous distribution. Agricultural Area is mainly found on the eastern and western parts of the region, with flat terrain, abundant water resources, and moderate temperatures. Built-up Area is the most concentrated but has an unbalanced distribution and the lowest quantity. (ii) Despite some discernible spatial and quantity changes at regional and county levels between 2000 and 2020, the general characteristics in HCA’s structure and distribution pattern have mainly remained consistent. (iii) Transitions between HCA types occur constantly, and the primary source type of the transitions differs from one another. Ecological Area and Bare Area form the sources of the most evident transitions. (iv) Agricultural Area and Built-up Area are more prone influence from some socioeconomic dynamics. By contrast, there is no evidence that socioeconomic factors directly affect Bare Area. As the first empirical study of the newly conceived concept, Human Critical Area, this paper sheds light on the renovation of geographic traditions of studying the evolution of the human-environment system through the lens of human activities-driven landscape changes

Plasma metabolomic profiling of dietary patterns associated with glucose metabolism status: The Maastricht Study

BACKGROUND: Glucose metabolism has been reported to be affected by dietary patterns, while the underlying mechanisms involved remain unclear. This study aimed to investigate the potential mediation role of circulating metabolites in relation to dietary patterns for prediabetes and type 2 diabetes. METHODS: Data was derived from The Maastricht Study that comprised of 3441 participants (mean age of 60 years) with 28% type 2 diabetes patients by design. Dietary patterns were assessed using a validated food frequency questionnaire (FFQ), and the glucose metabolism status (GMS) was defined according to WHO guidelines. Both cross-sectional and prospective analyses were performed for the circulating metabolome to investigate their associations and mediations with responses to dietary patterns and GMS. RESULTS: Among 226 eligible metabolite measures obtained from targeted metabolomics, 14 were identified to be associated and mediated with three dietary patterns (i.e. Mediterranean Diet (MED), Dietary Approaches to Stop Hypertension Diet (DASH), and Dutch Healthy Diet (DHD)) and overall GMS. Of these, the mediation effects of 5 metabolite measures were consistent for all three dietary patterns and GMS. Based on a 7-year follow-up, a decreased risk for apolipoprotein A1 (APOA1) and docosahexaenoic acid (DHA) (RR 0.60, 95% CI 0.55, 0.65; RR 0.89, 95% CI 0.83, 0.97, respectively) but an increased risk for ratio of ω-6 to ω-3 fatty acids (RR 1.29, 95% CI 1.05, 1.43) of type 2 diabetes were observed from prediabetes, while APOA1 showed a decreased risk of type 2 diabetes from normal glucose metabolism (NGM; RR 0.82, 95% CI 0.75, 0.89). CONCLUSIONS: In summary, this study suggests that adherence to a healthy dietary pattern (i.e. MED, DASH, or DHD) could affect the GMS through circulating metabolites, which provides novel insights into understanding the biological mechanisms of diet on glucose metabolism and leads to facilitating prevention strategy for type 2 diabetes

Plasma metabolomic profiling of dietary patterns associated with glucose metabolism status:The Maastricht Study

BACKGROUND: Glucose metabolism has been reported to be affected by dietary patterns, while the underlying mechanisms involved remain unclear. This study aimed to investigate the potential mediation role of circulating metabolites in relation to dietary patterns for prediabetes and type 2 diabetes. METHODS: Data was derived from The Maastricht Study that comprised of 3441 participants (mean age of 60 years) with 28% type 2 diabetes patients by design. Dietary patterns were assessed using a validated food frequency questionnaire (FFQ), and the glucose metabolism status (GMS) was defined according to WHO guidelines. Both cross-sectional and prospective analyses were performed for the circulating metabolome to investigate their associations and mediations with responses to dietary patterns and GMS. RESULTS: Among 226 eligible metabolite measures obtained from targeted metabolomics, 14 were identified to be associated and mediated with three dietary patterns (i.e. Mediterranean Diet (MED), Dietary Approaches to Stop Hypertension Diet (DASH), and Dutch Healthy Diet (DHD)) and overall GMS. Of these, the mediation effects of 5 metabolite measures were consistent for all three dietary patterns and GMS. Based on a 7-year follow-up, a decreased risk for apolipoprotein A1 (APOA1) and docosahexaenoic acid (DHA) (RR 0.60, 95% CI 0.55, 0.65; RR 0.89, 95% CI 0.83, 0.97, respectively) but an increased risk for ratio of ω-6 to ω-3 fatty acids (RR 1.29, 95% CI 1.05, 1.43) of type 2 diabetes were observed from prediabetes, while APOA1 showed a decreased risk of type 2 diabetes from normal glucose metabolism (NGM; RR 0.82, 95% CI 0.75, 0.89). CONCLUSIONS: In summary, this study suggests that adherence to a healthy dietary pattern (i.e. MED, DASH, or DHD) could affect the GMS through circulating metabolites, which provides novel insights into understanding the biological mechanisms of diet on glucose metabolism and leads to facilitating prevention strategy for type 2 diabetes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-022-02653-1

Traditional lifestyle factors partly mediate the association of socioeconomic position with intrahepatic lipid content:The Maastricht study

Background & Aims: Recent studies have unveiled an association between socioeconomic position (SEP) and intrahepatic lipid (IHL) content. The aim of this study was to examine to what extent traditional lifestyle factors mediate the relationship between SEP and IHL content, independent of aetiology, and non-alcoholic fatty liver disease (NAFLD). Methods: We used cross-sectional data derived from The Maastricht Study (N = 4,001; mean age: 60 years, 49% women, 32% low education level, 21% diabetes, 21% NAFLD). Education, income, and occupation were used as indicators of SEP. Physical activity (accelerometer), intake of total energy, alcohol, saturated fat, protein, vitamin E, dietary fibre, and fructose from sugar-sweetened beverages (SSBs) and fruit juice (food frequency questionnaires) were potential mediators. IHL content was quantified by magnetic resonance imaging. Age, sex, and type 2 diabetes were covariates. Multiple parallel mediation analyses (bootstraps = 10,000) were performed. Results: Individuals with a low education level had a 1.056-fold higher IHL content (95% CI: 1.03–1.08) and a 44% greater NAFLD risk (OR:1.44; 95% CI:1.18–1.77) compared with those with higher education levels. Approximately 8.9% of educational disparity in risk of IHL content was attributable to moderate-to-vigorous physical activity; 6.3% to fructose intake from SSBs; 5.5% to dietary fibre; and -23% to alcohol. Approximately 8.7% of educational disparity in risk of NAFLD was attributable to moderate-to-vigorous physical activity; and 7.7% to fructose intake from SSBs. However, the indirect effect of these mediators was small (0.998 for IHL content and 1.045 for NAFLD) in comparison to the total effect. Similar results were found when income and occupation were used as SEP indicators. Conclusions: Societal measures may alleviate the burden of NAFLD and further studies that identify mediators other than traditional lifestyle factors are warranted to define the relationship underlying SEP and IHL content. Impact and implications: Individuals with a low or medium level of education, income, or occupational status had more fat accumulation in their livers than individuals with a higher education, income, or occupational status. This difference may be attributed to the influence of unhealthy lifestyle factors, such as reduced physical activity and a higher intake of sugar-sweetened beverages among individuals with lower socioeconomic position. Nevertheless, other yet unknown factors may also play a role

Genetic susceptibility to nonalcoholic fatty liver disease and risk for pancreatic cancer:Mendelian randomization

BACKGROUND: There are conflicting data on whether nonalcoholic fatty liver disease (NAFLD) is associated with susceptibility to pancreatic cancer (PC). Using Mendelian randomization (MR), we investigated the relationship between genetic predisposition to NAFLD and risk for PC. METHODS: Data from genome-wide association studies within the Pancreatic Cancer Cohort Consortium (PanScan; cases n=5090, controls n=8733) and the Pancreatic Cancer Case Control Consortium (PanC4; cases n=4,163, controls n=3,792) were analyzed. We used data on 68 genetic variants with four different MR methods (inverse variance weighting [IVW], MR-Egger, simple median, and penalized weighted median) separately to predict genetic heritability of NAFLD. We then assessed the relationship between each of the four MR methods and PC risk, using logistic regression to calculate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for PC risk factors, including obesity and diabetes. RESULTS: No association was found between genetically predicted NAFLD and PC risk in the PanScan or PanC4 samples (e.g., PanScan, IVW OR=1.04, 95% CI: 0.88-1.22, MR-Egger OR=0.89, 95% CI: 0.65-1.21; PanC4, IVW OR=1.07, 95% CI: 0.90-1.27, MR-Egger OR=0.93, 95% CI: 0.67-1.28). None of the four MR methods indicated an association between genetically predicted NAFLD and PC risk in either sample. CONCLUSIONS: Genetic predisposition to NAFLD is not associated with PC risk. IMPACT: Given the close relationship between NAFLD and metabolic conditions, it is plausible that any association between NAFLD and PC might reflect host metabolic perturbations (e.g., obesity, diabetes, or metabolic syndrome) and does not necessarily reflect a causal relationship between NAFLD and PC

Genetic Susceptibility to Nonalcoholic Fatty Liver Disease and Risk for Pancreatic Cancer: Mendelian Randomization.

BACKGROUND: There are conflicting data on whether nonalcoholic fatty liver disease (NAFLD) is associated with susceptibility to pancreatic cancer. Using Mendelian randomization (MR), we investigated the relationship between genetic predisposition to NAFLD and risk for pancreatic cancer. METHODS: Data from genome-wide association studies (GWAS) within the Pancreatic Cancer Cohort Consortium (PanScan; cases n = 5,090, controls n = 8,733) and the Pancreatic Cancer Case Control Consortium (PanC4; cases n = 4,163, controls n = 3,792) were analyzed. We used data on 68 genetic variants with four different MR methods [inverse variance weighting (IVW), MR-Egger, simple median, and penalized weighted median] separately to predict genetic heritability of NAFLD. We then assessed the relationship between each of the four MR methods and pancreatic cancer risk, using logistic regression to calculate ORs and 95% confidence intervals (CI), adjusting for PC risk factors, including obesity and diabetes. RESULTS: No association was found between genetically predicted NAFLD and pancreatic cancer risk in the PanScan or PanC4 samples [e.g., PanScan, IVW OR, 1.04; 95% confidence interval (CI), 0.88-1.22; MR-Egger OR, 0.89; 95% CI, 0.65-1.21; PanC4, IVW OR, 1.07; 95% CI, 0.90-1.27; MR-Egger OR, 0.93; 95% CI, 0.67-1.28]. None of the four MR methods indicated an association between genetically predicted NAFLD and pancreatic cancer risk in either sample. CONCLUSIONS: Genetic predisposition to NAFLD is not associated with pancreatic cancer risk. IMPACT: Given the close relationship between NAFLD and metabolic conditions, it is plausible that any association between NAFLD and pancreatic cancer might reflect host metabolic perturbations (e.g., obesity, diabetes, or metabolic syndrome) and does not necessarily reflect a causal relationship between NAFLD and pancreatic cancer

Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2021

The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a suite of database resources to support worldwide research activities in both academia and industry. With the explosive growth of multiomics data, CNCB-NGDC is continually expanding, updating and enriching its core database resources through big data deposition, integration and translation. In the past year, considerable efforts have been devoted to 2019nCoVR, a newly established resource providing a global landscape of SARS-CoV-2 genomic sequences, variants, and haplotypes, as well as Aging Atlas, BrainBase, GTDB (Glycosyltransferases Database), LncExpDB, and TransCirc (Translation potential for circular RNAs). Meanwhile, a series of resources have been updated and improved, including BioProject, BioSample, GWH (Genome Warehouse), GVM (Genome Variation Map), GEN (Gene Expression Nebulas) as well as several biodiversity and plant resources. Particularly, BIG Search, a scalable, one-stop, cross-database search engine, has been significantly updated by providing easy access to a large number of internal and external biological resources from CNCB-NGDC, our partners, EBI and NCBI. All of these resources along with their services are publicly accessible at https://bigd.big.ac.cn