Association Between Multiple Metal(loid)s Exposure and Blood Lipid Levels: Evidence from a Cross-Sectional Study of Southeastern China.

Exposure to essential and toxic metals occurs simultaneously as a mixture in real-life. However, there is no consensus regarding the effects of co-exposure to multiple metal(loid)s (designated hereafter metals) on blood lipid levels. Thus, blood concentrations of six human essential metals and five toxic metals in 720 general populations from southeastern China were simultaneously determined as a measure of exposure. In addition, quantile g-computation, Bayesian kernel machine regression, elastic net regression, and generalized linear model were used to investigate both the joint and individual effects of exposure to this metal mixture on human blood lipid levels. The significant positive joint effect of exposure to this metal mixture on serum total cholesterol (TC) levels, rather than on serum triglycerides, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, Castelli risk index I, Castelli risk index II, atherogenic coefficient, and non-HDL-C levels, was found. In addition, the positive effect may be primarily driven by selenium (Se), lead (Pb), and mercury (Hg) exposure. In addition, on the effect of TC levels, the synergistic effect between Pb and Hg and the antagonistic effect between Se and Pb were identified. Our finding suggests that combined exposure to this metal mixture may affect human blood lipid levels. Therefore, reducing exposure to heavy metals, such as Pb and Hg, should be a priority for the general population. In addition, Se supplementation should also be considered with caution.

Co-exposure to low-dose lead, cadmium, and mercury promotes memory deficits in rats: Insights from the dynamics of dendritic spine pruning in brain development.

Lead (Pb), cadmium (Cd), and mercury (Hg) are environmentally toxic heavy metals that can be simultaneously detected at low levels in the blood of the general population. Although our previous studies have demonstrated neurodevelopmental toxicity upon co-exposure to these heavy metals at these low levels, the precise mechanisms remain largely unknown. Dendritic spines are the structural foundation of memory and undergo significant dynamic changes during development. This study focused on the dynamics of dendritic spines during brain development following Pb, Cd, and Hg co-exposure-induced memory impairment. First, the dynamic characteristics of dendritic spines in the prefrontal cortex were observed throughout the life cycle of normal rats. We observed that dendritic spines increased rapidly from birth to their peak value at weaning, followed by significant pruning and a decrease during adolescence. Dendritic spines tended to be stable until their loss in old age. Subsequently, a rat model of low-dose Pb, Cd, and Hg co-exposure from embryo to adolescence was established. The results showed that exposure to low doses of heavy metals equivalent to those detected in the blood of the general population impaired spatial memory and altered the dynamics of dendritic spine pruning from weaning to adolescence. Proteomic analysis of brain and blood samples suggested that differentially expressed proteins upon heavy metal exposure were enriched in dendritic spine-related cytoskeletal regulation and axon guidance signaling pathways and that cofilin was enriched in both of these pathways. Further experiments confirmed that heavy metal exposure altered actin cytoskeleton dynamics and disturbed the dendritic spine pruning-related LIM domain kinase 1-cofilin pathway in the rat prefrontal cortex. Our findings demonstrate that low-dose Pb, Cd, and Hg co-exposure may promote memory impairment by perturbing dendritic spine dynamics through dendritic spine pruning-related signaling pathways.

Association between multiple metal(loid)s exposure and renal function: a cross-sectional study from southeastern China.

In the real world, humans are exposed to multiple metal(loid)s (designated hereafter metals) that contain essential metals as well as toxic metals. Exposure to the metal mixture was assumed to be associated with renal function impairment; however, there is no consensus on available studies. Therefore, we here explored the association between multiple metals exposure and indicators of renal function in the general population from southeastern China. A total of 11 metals with 6 human essential metals and 5 toxic metals were determined in the selected 720 subjects. In addition, serum uric acid (SUA), serum creatinine (SCR), and the estimated glomerular filtration rate (eGFR) were measured or calculated as indicators of renal function. Using multiple flexible statistical models of generalized linear model, elastic net regression, and Bayesian kernel machine regression, the joint as well as the individual effect of metals within the mixture, and the interactions between metals were explored. When exposed to the metal mixture, the statistically non-significantly increased SUA, the significantly increased SCR, and the significantly declined eGFR were observed. In addition, the declined renal function may be primarily attributed to lead (Pb), arsenic (As), and nickel (Ni) exposure. Finally, interactions, such as the synergistic effect between Pb and Mo on SUA, whereas the antagonistic effect between Ni and Cd on SCR and eGFR were identified. Our finding suggests that combined exposure to multiple metals would impair renal function. Therefore, reducing exposure to toxic heavy metals of Pb, As, and Cd and limiting exposure to the human essential metal of Ni would protect renal function.

Hippocampal LIMK1-mediated Structural Synaptic Plasticity in Neurobehavioral Deficits Induced by a Low-dose Heavy Metal Mixture.

Humans are commonly exposed to the representative neurotoxic heavy metals lead (Pb), cadmium (Cd), and mercury (Hg). These three substances can be detected simultaneously in the blood of the general population. We have previously shown that a low-dose mixture of these heavy metals induces rat learning and memory impairment at human exposure levels, but the pathogenic mechanism is still unclear. LIM kinase 1 (LIMK1) plays a critical role in orchestrating synaptic plasticity during brain function and dysfunction. Hence, we investigated the role of LIMK1 activity in low-dose heavy metal mixture-induced neurobehavioral deficits and structural synaptic plasticity disorders. Our results showed that heavy metal mixture exposure altered rat fear responses and spatial learning at general population exposure levels and that these alterations were accompanied by downregulation of LIMK1 phosphorylation and structural synaptic plasticity dysfunction in rat hippocampal tissues and cultured hippocampal neurons. In addition, upregulation of LIMK1 phosphorylation attenuated heavy metal mixture-induced structural synaptic plasticity, dendritic actin dynamics, and cofilin phosphorylation damage. The potent LIMK1 inhibitor BMS-5 yielded similar results induced by heavy metal mixture exposure and aggravated these impairments. Our findings demonstrate that LIMK1 plays a crucial role in neurobehavioral deficits induced by low-dose heavy metal mixture exposure by suppressing structural synaptic plasticity.

Insight into the effect of a heavy metal mixture on neurological damage in rats through combined serum metabolomic and brain proteomic analyses.

The heavy metals lead (Pb), cadmium (Cd), and mercury (Hg) that cause neurocognitive impairment have been extensively studied. These elements typically do not exist alone in the environment; they are often found with other heavy metals and can enter the body through various routes, thereby impacting health. Our previous research showed that low Pb, Cd, and Hg levels cause neurobehavioral impairments in weaning and adult rats. However, little is known about the biomarkers and mechanisms underlying Pb, Cd, and Hg mixture-induced neurological impairments. A combined analysis of metabolomic and proteomic data may reveal heavy metal-induced alterations in metabolic and protein profiles, thereby improving our understanding of the molecular mechanisms underlying heavy metal-induced neurological impairments. Therefore, brain tissue and serum samples were collected from rats exposed to a Pb, Cd, and Hg mixture for proteomic and metabolomic analyses, respectively. The analysis revealed 363 differential proteins in the brain and 206 metabolites in serum uniquely altered in the Pb, Cd, and Hg mixture exposure group, compared to those of the control group. The main metabolic impacted pathways were unsaturated fatty acids biosynthesis, linoleic acid metabolism, phenylalanine metabolism, and tryptophan metabolism. We further identified that the levels of arachidonic acid (C20:4 n-3) and, adrenic acid (C22:4 n-3) were elevated and that kynurenic acid (KA) and quinolinic acid (QA) levels and the KA/QA ratio, were decreased in the group exposed to the Pb, Cd, and Hg mixture. A joint analysis of the proteome and metabolome showed that significantly altered proteins such as LPCAT3, SLC7A11, ASCL4, and KYAT1 may participate in the neurological impairments induced by the heavy metal mixture. Overall, we hypothesize that the dysregulation of ferroptosis and kynurenine pathways is associated with neurological damage due to chronic exposure to a heavy metal mixture.

Cognitive outcomes caused by low-level lead, cadmium, and mercury mixture exposure at distinct phases of brain development.

Contaminated water and food are the main sources of lead, cadmium, and mercury in the human body. Long-term and low-level ingestion of these toxic heavy metals may affect brain development and cognition. However, the neurotoxic effects of exposure to lead, cadmium, and mercury mixture (Pb + Cd + Hg) at different stages of brain development are rarely elucidated. In this study, different doses of low-level Pb + Cd + Hg were administered to Sprague-Dawley rats via drinking water during the critical stage of brain development, late stage, and after maturation, respectively. Our findings showed that Pb + Cd + Hg exposure decreased the density of memory- and learning-related dendritic spines in the hippocampus during the critical period of brain development, resulting in hippocampus-dependent spatial memory deficits. Only the density of learning-related dendritic spines was reduced during the late phase of brain development and a higher-dose of Pb + Cd + Hg exposure was required, which led to hippocampus-independent spatial memory abnormalities. Exposure to Pb + Cd + Hg after brain maturation revealed no significant change in dendritic spines or cognitive function. Further molecular analysis indicated that morphological and functional changes caused by Pb + Cd + Hg exposure during the critical phase were associated with PSD95 and GluA1 dysregulation. Collectively, the effects of Pb + Cd + Hg on cognition varied depending on the brain development stages.

Pregnancy and lactation mixed exposure to lead, cadmium, and mercury alters maternal-offspring single heavy metal load: A factorial design.

Environmental exposure to heavy metal mixture of lead (Pb), cadmium (Cd), and mercury (Hg) would induce hazardous health effects. However, there is a paucity of data on how exposure to heavy metal mixture alters the metabolic dynamics of individual metals. Considering that the dose plays a key role in determining the toxicity of heavy metals, we performed a factorial design with three heavy metals (Pb, Cd, and Hg) at low exposure levels. Female rats were exposed to Pb, Cd, and (or) Hg from successful mating until pup weaning. Their concentrations in maternal blood, breast milk, and postnatal day 0 (PND0) and PND21 offspring blood and whole brain were measured. Using ANOVA analysis, Pearson correlation, and structural equation model, we demonstrated the complex interactions among heavy metals during their absorption, mother-offspring transport, and target organ accumulation. Among all the explored samples, almost all the highest Pb, Cd, and Hg levels were observed in their respective single heavy metal exposure groups. In addition, Hg was found could antagonize the transport of Pb or Cd, when they cross the placental barrier and blood-brain barriers (BBB). However, the effect of Hg no longer presented when they are absorbed through the digestive system. The antagonistic effect of Pb on Cd was observed when they cross the placental barrier. In addition, Cd was also found to compete the transport pathway of Pb when they cross the BBB after birth. Compared to Pb and Hg, we found that the transport efficiency of Cd in the digestive system was lower, whereas the chelation of Cd by the placental barrier was better. This preliminary information may help researchers to explore the mechanism underlying the hazardous effects of heavy metal mixture exposure, or for regulatory agencies to revise guidelines for heavy metal exposure.

Stratified meta-analysis by ethnicity revealed that ADRB3 Trp64Arg polymorphism was associated with coronary artery disease in Asians, but not in Caucasians.

BACKGROUND: Previous studies demonstrated that ADRB3, beta-3 adrenergic receptor, participated in lipolysis and thermogenesis in adipose tissue. Consequently, this gene has attracted an increasing number of genetic studies examining its association with coronary artery disease (CAD) in different ethnicities in recent years, but no conclusion has been reached so far. The aim of this study was to explore whether the well-studied locus ADRB3 Trp64Arg in this gene confers a race-specific effect to CAD by conducting a stratified meta-analysis involving 15 independent studies and 11,802 subjects. METHODS: Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the strength of association. Publication bias was quantified and examined with Begg's funnel plot test and Egger's linear regression method. The overall meta-analysis or stratified meta-analysis by ethnicity was performed by using STATA 12.0 software. RESULTS: A total of 15 eligible studies involving 5779 CAD cases and 6023 health controls were included in this meta-analysis. The pooled results indicated that ADRB3 Trp64Arg polymorphism was significantly associated with an increased risk of CAD. Further stratified analysis by ethnicity revealed that ADRB3 Trp64Arg polymorphism was significantly associated with CAD in Asians (allelic: OR = 1.48, 95%CI 1.13-1.94, P = .005; homozygous: OR = 2.66, 95%CI 1.87-3.77, P < .001; recessive: OR = 2.46, 95%CI 1.74-3.47, P < .001), but not in Caucasians (allelic: OR = 1.09, 95%CI 0.93-1.27, P = .290; homozygous: OR = 1.31, 95%CI 0.61-2.86, P = .490; recessive: OR = 1.31, 95%CI 0.60-2.84, P = 2.494). CONCLUSIONS: This meta-analysis suggests that ADRB3 Trp64Arg polymorphism confers a race-specific effect to CAD.

A Seven-Long Non-coding RNA Signature Improves Prognosis Prediction of Lung Adenocarcinoma: An Integrated Competing Endogenous RNA Network Analysis.

Early and precise prediction is an important way to reduce the poor prognosis of lung adenocarcinoma (LUAD) patients. Nevertheless, the widely used tumor, node, and metastasis (TNM) staging system based on anatomical information only often could not achieve adequate performance on foreseeing the prognosis of LUAD patients. This study thus aimed to examine whether the long non-coding RNAs (lncRNAs), known highly involved in the tumorigenesis of LUAD through the competing endogenous RNAs (ceRNAs) mechanism, could provide additional information to improve prognosis prediction of LUAD patients. To prove the hypothesis, a dataset consisting of both RNA sequencing data and clinical pathological data, obtained from The Cancer Genome Atlas (TCGA) database, was analyzed. Then, differentially expressed RNAs (DElncRNAs, DEmiRNAs, and DEmRNAs) were identified and a lncRNA-miRNA-mRNA ceRNA network was constructed based on those differentially expressed RNAs. Functional enrichment analysis revealed that this ceRNA network was highly enriched in some cancer-associated signaling pathways. Next, lasso-Cox model was run 1,000 times to recognize the potential survival-related combinations of the candidate lncRNAs in the ceRNA network, followed by the "best subset selection" to further optimize these lncRNA-based combinations, and a seven-lncRNA prognostic signature with the best performance was determined. Based on the median risk score, LUAD patients could be well distinguished into high-/low-risk subgroups. The Kaplan-Meier survival curve showed that LUAD patients in the high-risk group had significantly shorter overall survival than those in the low-risk group (log-rank test P = 4.52 × 10-9). The ROC curve indicated that the clinical genomic model including both the TNM staging system and the signature had a superior performance in predicting the patients' overall survival compared to the clinical model with the TNM staging system only. Further stratification analysis suggested that the signature could work well in the different strata of the stage, gender, or age, rendering it to be a wide application. Finally, a ceRNA subnetwork related to the signature was extracted, demonstrating its high involvement in the tumorigenesis mechanism of LUAD. In conclusion, the present study established a lncRNA-based molecular signature, which can significantly improve prognosis prediction for LUAD patients.

Genome-Wide Association and Functional Studies Identify SCML4 and THSD7A as Novel Susceptibility Genes for Coronary Artery Disease.

OBJECTIVE: The genetic contribution to coronary artery disease (CAD) remains largely unclear. We combined genetic screening with functional characterizations to identify novel loci and candidate genes for CAD. APPROACH AND RESULTS: We performed genome-wide screening followed by multicenter validation in 8 cohorts consisting of 21 828 participants of Han ethnicity and identified 3 novel intragenic SNPs (single nucleotide polymorphisms), rs9486729 (SCML4 [Scm polycomb group protein-like 4]; odds ratio, 1.25; 95% CI, 1.17-1.34; P=3.51×10-11), rs17165136 (THSD7A [thrombospondin type 1 domain-containing 7A]; odds ratio 1.28; 95% CI, 1.21-1.35; P<1.00×10-25), and rs852787 (DAB1 [disabled-1]; odds ratio, 1.29; 95% CI, 1.21-1.38; P=2.02×10-14), associated with CAD with genome-wide significance. The risk allele of rs9486729 and protective allele of rs17165136 were associated with the decreased expression of their host genes, SCML4 and THSD7A, respectively, whereas rs852787 did not have transcriptional effects on any gene. Knockdown of SCML4 activated endothelial cells by increasing the expression of IL-6, E-selectin, and ICAM and weakened their antiapoptotic activity, whereas the knockdown of THSD7A had little effect on these endothelial cell functions but attenuated monocyte adhesion via decreasing the expression of ICAM, L-selectin, and ITGB2. We further showed that inhibiting the expression of SCML4 exacerbated endothelial dysfunction and vascular remodeling in a rat model with partial carotid ligation. CONCLUSIONS: We identify 3 novel loci associated with CAD and show that 2 genes, SCML4 and THSD7A, make functional contributions to atherosclerosis. How rs852787 and its host gene DAB1 are linked to CAD needs further studies.

Complex Segregation Analysis Provides Evidence for Autosomal Dominant Transmission in the Chinese Han Families with Ankylosing Spondylitis.

INTRODUCTION: Familial aggregation of ankylosing spondylitis (AS) has been frequently noticed. However, the mode of inheritance in AS remains poorly understood. Our aim was to determine the mode of inheritance best fitting the observed transmission pattern of AS families. METHODS: Families with 5 or more AS patients diagnosed with 1984 modified New York criteria were recruited. We performed complex segregation analysis for a binary trait in regressive multivariate logistic models. The inheritance models, including sporadic, major gene, environmental, general, and other 9 models, were compared by likelihood ratio tests and Akaike's Information Criterion. RESULTS: This research included 9 Chinese Han AS families with a total number of 315 persons, including 74 patients. First, familial association was determined. Sporadic with familial association model was rejected when compared with either the general model or the homogeneous general model (p < 0.001). The environmental model was also rejected when compared with general models (p < 0.02). Mendelian dominate mode fitted best in 5 AS families, while Tau AB free model best explained the mode of inheritance in these AS families. CONCLUSION: This study provided evidence in support of Mendelian dominant mode and firstly discovered a non-Mendelian mode called tau AB free inheritance mode in AS.

Identification of Risk Pathways and Functional Modules for Coronary Artery Disease Based on Genome-wide SNP Data.

Coronary artery disease (CAD) is a complex human disease, involving multiple genes and their nonlinear interactions, which often act in a modular fashion. Genome-wide single nucleotide polymorphism (SNP) profiling provides an effective technique to unravel these underlying genetic interplays or their functional involvements for CAD. This study aimed to identify the susceptible pathways and modules for CAD based on SNP omics. First, the Wellcome Trust Case Control Consortium (WTCCC) SNP datasets of CAD and control samples were used to assess the joint effect of multiple genetic variants at the pathway level, using logistic kernel machine regression model. Then, an expanded genetic network was constructed by integrating statistical gene-gene interactions involved in these susceptible pathways with their protein-protein interaction (PPI) knowledge. Finally, risk functional modules were identified by decomposition of the network. Of 276 KEGG pathways analyzed, 6 pathways were found to have a significant effect on CAD. Other than glycerolipid metabolism, glycosaminoglycan biosynthesis, and cardiac muscle contraction pathways, three pathways related to other diseases were also revealed, including Alzheimer's disease, non-alcoholic fatty liver disease, and Huntington's disease. A genetic epistatic network of 95 genes was further constructed using the abovementioned integrative approach. Of 10 functional modules derived from the network, 6 have been annotated to phospholipase C activity and cell adhesion molecule binding, which also have known functional involvement in Alzheimer's disease. These findings indicate an overlap of the underlying molecular mechanisms between CAD and Alzheimer's disease, thus providing new insights into the molecular basis for CAD and its molecular relationships with other diseases.

Association between apolipoprotein B EcoRI polymorphisms and coronary heart disease : A meta-analysis.

OBJECTIVE: The study was carried out to examine the association between apolipoprotein B (ApoB) EcoRI polymorphism (E- vs. E+) (rs1042031) and coronary heart disease (CHD) risk by systematically analyzing multiple independent studies. METHODS: The Hardy-Weinberg equilibrium (HWE) test was applied to assess genotype frequency distribution in healthy controls. The quality of the studies was assessed using the Newcastle-Ottawa scale (NOS). Power analysis was performed with Power and Precision V4 software. A fixed effect model was used because no deviation from homogeneity was found. Publication bias was quantified and examined with Begg's funnel plot test and Egger's linear regression method. The meta-analysis was performed by Stata 12.0 software. RESULTS: A total of 21 eligible association studies were merged in this meta-analysis and the pooled sample consisted of 2994 CHD patients and 3258 healthy controls. No significant publication bias and heterogeneity were observed in these studies. The pooled odds ratio (OR) and 95% confidence interval (CI) of E- vs. E+ were 1.18 (1.06-1.32). The pooled OR (95% CI) of E+ E- + E- E- vs. E+ E+ was 1.18 (1.04-1.34). CONCLUSIONS: This meta-analysis indicated that ApoB EcoRI confers a moderate risk for CHD and the E- allele at this locus might be a susceptibility allele for the development of CHD.

Association Between Apolipoprotein B XbaI Polymorphism and Coronary Heart Disease in Han Chinese Population: A Meta-Analysis.

OBJECTIVE: To examine the association between apolipoprotein B (ApoB) XbaI polymorphisms (rs693) and coronary heart disease (CHD) risk among the Han Chinese population by systematically analyzing multiple independent studies. METHODS: The Hardy-Weinberg equilibrium test was applied to check genetic equilibrium among genotypes for the selected literatures. The quality of the studies was assessed by using the NewcastleOttawa Scale. Power analysis was performed with Power and Precision V4 software. A fixed or random effect model was used on the basis of heterogeneity. Publication bias was quantified and examined with Begg's funnel plot test and Egger's linear regression test. The meta-analysis was performed by Stata 12.0 software. RESULTS: A total of 10 eligible association studies were included in this meta-analysis, and the pooled sample consisted of 1195 CHD patients and 1178 health controls. No consistent inference regarding publication bias for the included studies was obtained by using the two above-mentioned methods. The pooled odds ratios (95% confidence intervals [CIs]) for X(-) versus X(+) allele and X(+)X(+) + X(+)X(-) versus X(-)X(-) genotype were 2.25 (1.40-3.62) and 2.21 (1.39-3.50), respectively. CONCLUSIONS: This meta-analysis indicated that ApoB XbaI allele confers a significant risk towards the development of CHD among the Han Chinese population.

Molecular Basis of Gene-Gene Interaction: Cyclic Cross-Regulation of Gene Expression and Post-GWAS Gene-Gene Interaction Involved in Atrial Fibrillation.

Atrial fibrillation (AF) is the most common cardiac arrhythmia at the clinic. Recent GWAS identified several variants associated with AF, but they account for <10% of heritability. Gene-gene interaction is assumed to account for a significant portion of missing heritability. Among GWAS loci for AF, only three were replicated in the Chinese Han population, including SNP rs2106261 (G/A substitution) in ZFHX3, rs2200733 (C/T substitution) near PITX2c, and rs3807989 (A/G substitution) in CAV1. Thus, we analyzed the interaction among these three AF loci. We demonstrated significant interaction between rs2106261 and rs2200733 in three independent populations and combined population with 2,020 cases/5,315 controls. Compared to non-risk genotype GGCC, two-locus risk genotype AATT showed the highest odds ratio in three independent populations and the combined population (OR=5.36 (95% CI 3.87-7.43), P=8.00×10-24). The OR of 5.36 for AATT was significantly higher than the combined OR of 3.31 for both GGTT and AACC, suggesting a synergistic interaction between rs2106261 and rs2200733. Relative excess risk due to interaction (RERI) analysis also revealed significant interaction between rs2106261 and rs2200733 when exposed two copies of risk alleles (RERI=2.87, P<1.00×10-4) or exposed to one additional copy of risk allele (RERI=1.29, P<1.00×10-4). The INTERSNP program identified significant genotypic interaction between rs2106261 and rs2200733 under an additive by additive model (OR=0.85, 95% CI: 0.74-0.97, P=0.02). Mechanistically, PITX2c negatively regulates expression of miR-1, which negatively regulates expression of ZFHX3, resulting in a positive regulation of ZFHX3 by PITX2c; ZFHX3 positively regulates expression of PITX2C, resulting in a cyclic loop of cross-regulation between ZFHX3 and PITX2c. Both ZFHX3 and PITX2c regulate expression of NPPA, TBX5 and NKX2.5. These results suggest that cyclic cross-regulation of gene expression is a molecular basis for gene-gene interactions involved in genetics of complex disease traits.

Knowledge-based analysis of genetic associations of rheumatoid arthritis to inform studies searching for pleiotropic genes: a literature review and network analysis.

INTRODUCTION: Pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. Gene variants directly affect the normal processes of a series of physiological and biochemical reactions, and therefore cause a variety of diseases traits to be changed accordingly. Moreover, a shared genetic susceptibility mechanism may exist between different diseases. Therefore, shared genes, with pleiotropic effects, are important to understand the sharing pathogenesis and hence the mechanisms underlying comorbidity. METHODS: In this study, we proposed combining genome-wide association studies (GWAS) and public knowledge databases to search for potential pleiotropic genes associated with rheumatoid arthritis (RA) and eight other related diseases. Here, a GWAS-based network analysis is used to recognize risk genes significantly associated with RA. These RA risk genes are re-extracted as potential pleiotropic genes if they have been proved to be susceptible genes for at least one of eight other diseases in the OMIM or PubMed databases. RESULTS: In total, we extracted 116 potential functional pleiotropic genes for RA and eight other diseases, including five hub pleiotropic genes, BTNL2, HLA-DRA, NOTCH4, TNXB, and C6orf10, where BTNL2, NOTCH4, and C6orf10 are novel pleiotropic genes identified by our analysis. CONCLUSIONS: This study demonstrates that pleiotropy is a common property of genes associated with disease traits. Our results ascertained the shared genetic risk profiles that predisposed individuals to RA and other diseases, which could have implications for identification of molecular targets for drug development, and classification of diseases.

Association of DRD3, COMT, and SLC6A4 Gene Polymorphisms with Type 2 Diabetes in Southern Chinese: A Hospital-Based Case-Control Study.

AIM: The aim of this study was to assess the associations of six single nucleotide polymorphisms (SNPs) of three genes (DRD3, COMT, and SCL6A4) with type 2 diabetes mellitus (T2DM) in Southern Chinese. SUBJECTS AND METHODS: Five hundred ninety-five cases with T2DM and 725 healthy controls of Han origin were recruited from six hospitals in Guangdong Province, Southern China. Fasting serum concentrations of markers of interest (total cholesterol, triglyceride, plasma glucose, etc.) were measured in hospitals. SNP genotyping was performed using a custom-by-design 2-×48-Plex SNPscan™ kit (Genesky Biotechnologies Inc., Shanghai, China). Single-point SNP analysis, haplotype analysis, and SNP-SNP interactions were carried out. RESULTS: SNP rs4646312 in COMT achieved statistical significance in both allelic association and genotypic association and even after adjusting covariates (odds ratio [OR]=1.26; 95% confidence interval [CI], 1.04-1.53; P=0.021). Two haplotypes consisting of rs4646312 and rs4680 were also significantly associated with T2DM, of which C-G was a protective haplotype for T2DM (OR=0.83; 95% CI, 0.70-0.98; P=0.029), whereas T-A was a risk one (OR=1.23, 95% CI, 1.03-1.46; P=0.022). Interaction analysis identified a significant epistatic effect between rs4680 in COMT and rs2066713 in SCL6A4 after adjusting for covariates (OR=3.59, 95% CI, 1.72-7.48; P=0.001 for dominant-dominant model). However, only the interaction between rs4680 and rs2066713 was significant, and haplotype T-A showed a marginally increased risk after Bonferroni correction. CONCLUSIONS: The genetic polymorphisms in COMT and SCL6A4 confer significant effects in joint actions to T2DM in Southern Chinese.

Genome-wide linkage scan identifies two novel genetic loci for coronary artery disease: in GeneQuest families.

Coronary artery disease (CAD) is the leading cause of death worldwide. Recent genome-wide association studies (GWAS) identified >50 common variants associated with CAD or its complication myocardial infarction (MI), but collectively they account for <20% of heritability, generating a phenomena of "missing heritability". Rare variants with large effects may account for a large portion of missing heritability. Genome-wide linkage studies of large families and follow-up fine mapping and deep sequencing are particularly effective in identifying rare variants with large effects. Here we show results from a genome-wide linkage scan for CAD in multiplex GeneQuest families with early onset CAD and MI. Whole genome genotyping was carried out with 408 markers that span the human genome by every 10 cM and linkage analyses were performed using the affected relative pair analysis implemented in GENEHUNTER. Affected only nonparametric linkage (NPL) analysis identified two novel CAD loci with highly significant evidence of linkage on chromosome 3p25.1 (peak NPL  = 5.49) and 3q29 (NPL  = 6.84). We also identified four loci with suggestive linkage on 9q22.33, 9q34.11, 17p12, and 21q22.3 (NPL  = 3.18-4.07). These results identify novel loci for CAD and provide a framework for fine mapping and deep sequencing to identify new susceptibility genes and novel variants associated with risk of CAD.

Pathway-based analysis tools for complex diseases: a review.

Genetic studies are traditionally based on single-gene analysis. The use of these analyses can pose tremendous challenges for elucidating complicated genetic interplays involved in complex human diseases. Modern pathway-based analysis provides a technique, which allows a comprehensive understanding of the molecular mechanisms underlying complex diseases. Extensive studies utilizing the methods and applications for pathway-based analysis have significantly advanced our capacity to explore large-scale omics data, which has rapidly accumulated in biomedical fields. This article is a comprehensive review of the pathway-based analysis methods-the powerful methods with the potential to uncover the biological depths of the complex diseases. The general concepts and procedures for the pathway-based analysis methods are introduced and then, a comprehensive review of the major approaches for this analysis is presented. In addition, a list of available pathway-based analysis software and databases is provided. Finally, future directions and challenges for the methodological development and applications of pathway-based analysis techniques are discussed. This review will provide a useful guide to dissect complex diseases.

Genomic scan reveals loci under altitude adaptation in Tibetan and Dahe pigs.

High altitude environments are of particular interest in the studies of local adaptation as well as their implications in physiology and clinical medicine in human. Some Chinese pig breeds, such as Tibetan pig (TBP) that is well adapted to the high altitude and Dahe pig (DHP) that dwells at the moderate altitude, provide ideal materials to study local adaptation to altitudes. Yet, it is still short of in-depth analysis and understanding of the genetic adaptation to high altitude in the two pig populations. In this study we conducted a genomic scan for selective sweeps using FST to identify genes showing evidence of local adaptations in TBP and DHP, with Wuzhishan pig (WZSP) as the low-altitude reference. Totally, we identified 12 specific selective genes (CCBE1, F2RL1, AGGF1, ZFPM2, IL2, FGF5, PLA2G4A, ADAMTS9, NRBF2, JMJD1C, VEGFC and ADAM19) for TBP and six (OGG1, FOXM, FLT3, RTEL1, CRELD1 and RHOG) for DHP. In addition, six selective genes (VPS13A, GNA14, GDAP1, PARP8, FGF10 and ADAMTS16) were shared by the two pig breeds. Among these selective genes, three (VEGFC, FGF10 and ADAMTS9) were previously reported to be linked to the local adaptation to high altitudes in pigs, while many others were newly identified by this study. Further bioinformatics analysis demonstrated that majority of these selective signatures have some biological functions relevant to the altitude adaptation, for examples, response to hypoxia, development of blood vessels, DNA repair and several hematological involvements. These results suggest that the local adaptation to high altitude environments is sophisticated, involving numerous genes and multiple biological processes, and the shared selective signatures by the two pig breeds may provide an effective avenue to identify the common adaptive mechanisms to different altitudes.