Identification of an alternative short ARID5B isoform associated with B-ALL survival.

Utilizing RNA sequence (RNA-Seq) splice junction data from a cohort of 1841 B-cell acute lymphoblastic leukemia (B-ALL) patients we define transcriptionally distinct isoforms of ARID5B, a risk-associated gene identified in genome wide association studies (GWAS), which associate with disease survival. Short (S) and long (L) ARID5B transcripts, which differ in an encoded BAH-like chromatin interaction domain, show remarkable correlation to the isoform splicing pattern. Testing of the ARID5B proximal promoter of the S & L isoforms indicated that both are functionally independent in luciferase reporter assays. Increased short isoform expression is associated with decreased event-free and overall survival. The abundance of short and long transcripts strongly correlates to B-ALL prognostic stratification, where B-ALL subtypes with poor outcomes express a higher proportion of the S-isoform. These data demonstrate that the analysis of independent promoters and alternative splicing events are essential for improved risk stratification and a more complete understanding of disease pathology.

Transcriptome Sequencing Allows Comprehensive Genomic Characterization of Pediatric B-Acute Lymphoblastic Leukemia in an Academic Clinical Laboratory.

Studies have shown the power of transcriptome sequencing [RNA sequencing (RNA-Seq)] in identifying known and novel oncogenic drivers and molecular subtypes of B-acute lymphoblastic leukemia (B-ALL). The current study investigated whether the clinically validated RNA-Seq assay, coupled with a custom analysis pipeline, could be used for a comprehensive B-ALL classification. Following comprehensive clinical testing, RNA-Seq was performed on 76 retrospective B-ALL cases, 28 of which had known and 48 had undetermined subtype. Subtypes were accurately identified in all 28 known cases, and in 38 of 48 unknown cases (79%). The subtypes of the unknown cases included the following: PAX5alt (n = 12), DUX4-rearranged (n = 6), Philadelphia chromosome-like (n = 5), low hyperdiploid (n = 4), ETV6::RUNX1-like (n = 3), MEF2D-rearranged (n = 2), PAX5 P80R (n = 2), ZEB2/CEBP (n = 1), NUTM1-rearranged (n = 1), ZNF384-rearranged (n = 1), and TCF3::PBX1 (n = 1). In 15 of 38 cases (39%), classification based on expression profile was corroborated by detection of subtype-defining oncogenic drivers missed by clinical testing. RNA-Seq analysis also detected large copy number abnormalities, oncogenic hot-spot sequence variants, and intragenic IKZF1 deletions. This pilot study confirms the feasibility of implementing an RNA-Seq workflow for clinical diagnosis of molecular subtypes in pediatric B-ALL, reinforcing that RNA-Seq represents a promising global genomic assay for this heterogeneous leukemia.

MD-ALL: an integrative platform for molecular diagnosis of B-acute lymphoblastic leukemia.

B-acute lymphoblastic leukemia (B-ALL) consists of dozens of subtypes defined by distinct gene expression profiles (GEPs) and various genetic lesions. With the application of transcriptome sequencing (RNA-seq), multiple novel subtypes have been identified, which lead to an advanced B-ALL classification and risk-stratification system. However, the complexity of analyzing RNA-seq data for B-ALL classification hinders the implementation of the new B-ALL taxonomy. Here, we introduce MD-ALL (Molecular Diagnosis of ALL), an integrative platform featuring sensitive and accurate B-ALL classification based on GEPs and sentinel genetic alterations from RNA-seq data. In this study, we systematically analyzed 2,955 B-ALL RNA-seq samples and generated a reference dataset representing all the reported B-ALL subtypes. Using multiple machine learning algorithms, we identified the feature genes and then established highly sensitive and accurate models for B-ALL classification using either bulk or single-cell RNA-seq data. Importantly, this platform integrates multiple aspects of key genetic lesions acquired from RNAseq data, which include sequence mutations, large-scale copy number variations, and gene rearrangements, to perform comprehensive and definitive B-ALL classification. Through validation in a hold-out cohort of 974 samples, our models demonstrated superior performance for B-ALL classification compared with alternative tools. Moreover, to ensure accessibility and user-friendly navigation even for users with limited or no programming background, we developed an interactive graphical user interface for this MD-ALL platform, using the R Shiny package. In summary, MD-ALL is a user-friendly B-ALL classification platform designed to enable integrative, accurate, and comprehensive B-ALL subtype classification. MD-ALL is available from https://github.com/gu-lab20/MD-ALL.

MD-ALL: an Integrative Platform for Molecular Diagnosis of B-cell Acute Lymphoblastic Leukemia.

B-cell acute lymphoblastic leukemia (B-ALL) consists of dozens of subtypes defined by distinct gene expression profiles (GEPs) and various genetic lesions. With the application of transcriptome sequencing (RNA-seq), multiple novel subtypes have been identified, which lead to an advanced B-ALL classification and risk-stratification system. However, the complexity of analyzing RNA-seq data for B-ALL classification hinders the implementation of the new B-ALL taxonomy. Here, we introduce MD-ALL (Molecular Diagnosis of ALL), a user-friendly platform featuring sensitive and accurate B-ALL classification based on GEPs and sentinel genetic alterations. In this study, we systematically analyzed 2,955 B-ALL RNA-seq samples and generated a reference dataset representing all the reported B-ALL subtypes. Using multiple machine learning algorithms, we identified the feature genes and then established highly accurate models for B-ALL classification using either bulk or single-cell RNA-seq data. Importantly, this platform integrates the key genetic lesions, including sequence mutations, large-scale copy number variations, and gene rearrangements, to perform comprehensive and definitive B-ALL classification. Through validation in a hold-out cohort of 974 samples, our models demonstrated superior performance for B-ALL classification compared with alternative tools. In summary, MD-ALL is a user-friendly B-ALL classification platform designed to enable integrative, accurate, and comprehensive B-ALL subtype classification.

Isoform-specific knockdown of long and intermediate prolactin receptors interferes with evolution of B-cell neoplasms.

Prolactin (PRL) is elevated in B-cell-mediated lymphoproliferative diseases and promotes B-cell survival. Whether PRL or PRL receptors drive the evolution of B-cell malignancies is unknown. We measure changes in B cells after knocking down the pro-proliferative, anti-apoptotic long isoform of the PRL receptor (LFPRLR) in vivo in systemic lupus erythematosus (SLE)- and B-cell lymphoma-prone mouse models, and the long plus intermediate isoforms (LF/IFPRLR) in human B-cell malignancies. To knockdown LF/IFPRLRs without suppressing expression of the counteractive short PRLR isoforms (SFPRLRs), we employ splice-modulating DNA oligomers. In SLE-prone mice, LFPRLR knockdown reduces numbers and proliferation of pathogenic B-cell subsets and lowers the risk of B-cell transformation by downregulating expression of activation-induced cytidine deaminase. LFPRLR knockdown in lymphoma-prone mice reduces B-cell numbers and their expression of BCL2 and TCL1. In overt human B-cell malignancies, LF/IFPRLR knockdown reduces B-cell viability and their MYC and BCL2 expression. Unlike normal B cells, human B-cell malignancies secrete autocrine PRL and often express no SFPRLRs. Neutralization of secreted PRL reduces the viability of B-cell malignancies. Knockdown of LF/IFPRLR reduces the growth of human B-cell malignancies in vitro and in vivo. Thus, LF/IFPRLR knockdown is a highly specific approach to block the evolution of B-cell neoplasms.

Prenatal metabolomic profiles mediate the effect of maternal obesity on early childhood growth trajectories and obesity risk: the Conditions Affecting Neurocognitive Development and Learning in Early Childhood (CANDLE) Study.

BACKGROUND: Maternal prepregnancy obesity is an important risk factor for offspring obesity, which may partially operate through prenatal programming mechanisms. OBJECTIVES: The study aimed to systematically identify prenatal metabolomic profiles mediating the intergenerational transmission of obesity. METHODS: We included 450 African-American mother-child pairs from the Conditions Affecting Neurocognitive Development and Learning in Early Childhood (CANDLE) Study pregnancy cohort. LC-MS was used to conduct metabolomic profiling on maternal plasma samples of the second trimester. The childhood growth outcomes of interest included BMI trajectories from birth to age 4 y (rising-high-, moderate-, and low-BMI trajectories) as well as overweight/obesity (OWO) risk at age 4 y. Mediation analysis was conducted to identify metabolite mediators linking maternal OWO and childhood growth outcomes. The potential causal effects of maternal OWO on metabolite mediators were examined using the Mendelian randomization (MR) method. RESULTS: Among the 880 metabolites detected in the maternal plasma during pregnancy, 14 and 11 metabolites significantly mediated the effects of maternal prepregnancy OWO on childhood BMI trajectories and the OWO risk at age 4 y, respectively, and 5 mediated both outcomes. The MR analysis suggested 6 of the 20 prenatal metabolite mediators might be causally influenced by maternal prepregnancy OWO, most of which are from the pathways related to the metabolism of amino acids (hydroxyasparagine, glutamate, and homocitrulline), sterols (campesterol), and nucleotides (N2,N2-dimethylguanosine). CONCLUSIONS: Our study provides further evidence that prenatal metabolomic profiles might mediate the effect of maternal OWO on early childhood growth trajectories and OWO risk in offspring. The metabolic pathways, including identified metabolite mediators, might provide novel intervention targets for preventing the intrauterine development of obesity in the offspring of mothers with obesity.

RNAseqCNV: analysis of large-scale copy number variations from RNA-seq data.

Transcriptome sequencing (RNA-seq) is widely used to detect gene rearrangements and quantitate gene expression in acute lymphoblastic leukemia (ALL), but its utility and accuracy in identifying copy number variations (CNVs) has not been well described. CNV information inferred from RNA-seq can be highly informative to guide disease classification and risk stratification in ALL due to the high incidence of aneuploid subtypes within this disease. Here we describe RNAseqCNV, a method to detect large scale CNVs from RNA-seq data. We used models based on normalized gene expression and minor allele frequency to classify arm level CNVs with high accuracy in ALL (99.1% overall and 98.3% for non-diploid chromosome arms, respectively), and the models were further validated with excellent performance in acute myeloid leukemia (accuracy 99.8% overall and 99.4% for non-diploid chromosome arms). RNAseqCNV outperforms alternative RNA-seq based algorithms in calling CNVs in the ALL dataset, especially in samples with a high proportion of CNVs. The CNV calls were highly concordant with DNA-based CNV results and more reliable than conventional cytogenetic-based karyotypes. RNAseqCNV provides a method to robustly identify copy number alterations in the absence of DNA-based analyses, further enhancing the utility of RNA-seq to classify ALL subtype.

Error-prone, stress-induced 3' flap-based Okazaki fragment maturation supports cell survival.

How cells with DNA replication defects acquire mutations that allow them to escape apoptosis under environmental stress is a long-standing question. Here, we report that an error-prone Okazaki fragment maturation (OFM) pathway is activated at restrictive temperatures in rad27Δ yeast cells. Restrictive temperature stress activated Dun1, facilitating transformation of unprocessed 5' flaps into 3' flaps, which were removed by 3' nucleases, including DNA polymerase δ (Polδ). However, at certain regions, 3' flaps formed secondary structures that facilitated 3' end extension rather than degradation, producing alternative duplications with short spacer sequences, such as pol3 internal tandem duplications. Consequently, little 5' flap was formed, suppressing rad27Δ-induced lethality at restrictive temperatures. We define a stress-induced, error-prone OFM pathway that generates mutations that counteract replication defects and drive cellular evolution and survival.

Associations of prenatal metabolomics profiles with early childhood growth trajectories and obesity risk in African Americans: the CANDLE study.

OBJECTIVE: Prenatal metabolomics profiles, providing measures of in utero nutritional and environmental exposures, may improve the prediction of childhood outcomes. We aimed to identify prenatal plasma metabolites associated with early childhood body mass index (BMI) trajectories and overweight/obesity risk in offspring. METHODS: This study included 450 African American mother-child pairs from the Conditions Affecting Neurocognitive Development and Learning in Early Childhood Study. An untargeted metabolomics analysis was performed on the mothers' plasma samples collected during the second trimester. The children's BMI-z-score trajectories from birth to age 4 [rising-high- (9.8%), moderate- (68.2%), and low-BMI (22.0%)] and overweight/obesity status at age 4 were the main outcomes. The least absolute shrinkage and selection operator (LASSO) was used to select the prenatal metabolites associated with childhood outcomes. RESULTS: The mothers were 24.5 years old on average at recruitment, 76.4% having education less than 12 years and 80.0% with Medicaid or Medicare. In LASSO, seven and five prenatal metabolites were associated with the BMI-z-score trajectories and overweight/obese at age 4, respectively. These metabolites are mainly from/relevant to the pathways of steroid biosynthesis, amino acid metabolism, vitamin B complex, and xenobiotics metabolism (e.g., caffeine and nicotine). The odds ratios (95% CI) associated with a one SD increase in the prenatal metabolite risk scores (MRSs) constructed from the LASSO-selected metabolites were 2.97 (1.95-4.54) and 2.03 (1.54-2.67) for children being in the rising-high-BMI trajectory group and overweight/obesity at age 4, respectively. The MRSs significantly improved the risk prediction for childhood outcomes beyond traditional prenatal risk factors. The increase (95% CI) in the area under the receiver operating characteristic curves were 0.10 (0.03-0.18) and 0.07 (0.02-0.12) for the rising-high-BMI trajectory (P = 0.005) and overweight/obesity at age 4 (P = 0.007), respectively. CONCLUSIONS: Prenatal metabolomics profiles advanced prediction of early childhood growth trajectories and obesity risk in offspring.

Effects of Maternal Dietary Patterns during Pregnancy on Early Childhood Growth Trajectories and Obesity Risk: The CANDLE Study.

We investigated the associations between maternal dietary patterns during pregnancy and early childhood growth trajectories and overweight/obesity risk in offspring. Maternal diet was assessed using a food frequency questionnaire during the second trimester, and dietary patterns were derived by reduced rank regression. The associations between maternal dietary pattern scores and body mass index (BMI) trajectories from birth to age four (rising-high, moderate, and low BMI trajectories) as well as overweight/obesity risk at age four were analyzed (n = 1257). Two maternal dietary patterns were identified. The fast food pattern included a higher intake of fried chicken and fish, fruit juices, mayonnaise, and sugar-sweetened beverages, while the processed food pattern included a higher intake of dairy, salad dressing, processed meat, and cold breakfast cereal. Women with greater adherence to the fast food pattern were more likely to have children in the rising-high BMI trajectory group [OR (95% CI) = 1.32 (1.07-1.62); p = 0.008] or having overweight/obesity at age four [OR (95% CI) = 1.31 (1.11-1.54); p = 0.001]. The processed food pattern was not associated with these outcomes. The maternal dietary pattern during pregnancy represented by fried foods and sugar-sweetened beverages may contribute to rapid early childhood growth and increased risk for obesity in offspring.

Maternal metabolic factors during pregnancy predict early childhood growth trajectories and obesity risk: the CANDLE Study.

BACKGROUND: We investigated the individual and additive effects of three modifiable maternal metabolic factors, including pre-pregnancy overweight/obesity, gestational weight gain (GWG), and gestational diabetes mellitus (GDM), on early childhood growth trajectories and obesity risk. METHODS: A total of 1425 mother-offspring dyads (953 black and 472 white) from a longitudinal birth cohort were included in this study. Latent class growth modeling was performed to identify the trajectories of body mass index (BMI) from birth to 4 years in children. Poisson regression models were used to examine the associations between the maternal metabolic risk factors and child BMI trajectories and obesity risk at 4 years. RESULTS: We identified three discrete BMI trajectory groups, characterized as rising-high-BMI (12.6%), moderate-BMI (61.0%), or low-BMI (26.4%) growth. Both maternal pre-pregnancy obesity (adjusted relative risk [adjRR] = 1.96; 95% confidence interval [CI]: 1.36-2.83) and excessive GWG (adjRR = 1.71, 95% CI: 1.13-2.58) were significantly associated with the rising-high-BMI trajectory, as manifested by rapid weight gain during infancy and a stable but high BMI until 4 years. All three maternal metabolic indices were significantly associated with childhood obesity at age 4 years (adjRR for pre-pregnancy obesity = 2.24, 95% CI: 1.62-3.10; adjRR for excessive GWG = 1.46, 95% CI: 1.01-2.09; and adjRR for GDM = 2.14, 95% = 1.47-3.12). In addition, risk of rising-high BMI trajectory or obesity at age 4 years was stronger among mothers with more than one metabolic risk factor. We did not observe any difference in these associations by race. CONCLUSION: Maternal pre-pregnancy obesity, excessive GWG, and GDM individually and jointly predict rapid growth and obesity at age 4 years in offspring, regardless of race. Interventions targeting maternal obesity and metabolism may prevent or slow the rate of development of childhood obesity.

Genetic variants of cGMP-dependent protein kinase genes and salt sensitivity of blood pressure: the GenSalt study.

Genetic mechanisms involved in the susceptibility to salt sensitivity have not been completely clarified. This study aimed to comprehensively examine the association between genetic variants in the cyclic guanosine monophosphate (cGMP)-dependent protein kinase (PKG/PRKG) genes and blood pressure (BP) responses to dietary sodium intervention in a Chinese population. A 7-day low-sodium intervention followed by a 7-day high-sodium intervention was conducted among 1906 Han participants from rural areas of northern China. Nine BP measurements were obtained at baseline and each intervention using a random-zero sphygmomanometer. Linear mixed-effect models were used to assess the additive association of 213 tag single-nucleotide polymorphisms (SNPs) in two PRKG genes (PRKG1 and PRKG2) with salt sensitivity phenotypes. Gene-based analyses were conducted using the truncated product method. The Bonferroni method was used to adjust for multiple testing. Mean systolic BP response to low-sodium intervention significantly decreased with the number of minor T allele of marker rs10997916 in PRKG1 (P = 2.4 × 10-5). Mean systolic BP responses (95% confidence interval) among those with genotypes CC, CT, and TT were -5.6 (-6.0, -5.3), -3.7 (-4.7, -2.8), and -1.3 (-4.6, 2.0) mmHg, respectively, during the low-sodium intervention. Gene-based analyses demonstrated that PRKG1 was significantly associated with systolic BP response to low-sodium intervention (P = 1.2 × 10-3), whereas PRKG2 was nominally significantly associated with diastolic BP responses to high-sodium intervention (P = 2.6 × 10-2). The current study suggested a significant association of genetic variants in the PRKG genes with variation of BP response to dietary sodium intake in Han Chinese population. These novel findings merit further replication in future.

Characterization of LncRNA expression profile and identification of novel LncRNA biomarkers to diagnose coronary artery disease.

BACKGROUND AND AIMS: Dysregulation of long non-coding RNAs (lncRNAs) has been proven to be involved in the pathogenesis of coronary artery disease (CAD). However, it remains to be extensively explored. Thus, the present study aims to study expression patterns, biological functions, and diagnostic value of lncRNAs in CAD. METHODS: Using microarray, we performed the transcriptome-wide lncRNA and mRNAs expression profile of peripheral blood mononuclear cells (PBMCs) of 93 CAD patients and 48 healthy controls. Gene Ontology (GO) and pathway analysis for differentially expressed mRNAs were used to investigate underlying biological associations of differentially expressed lncRNAs, and path-net was created to depict interactions of significant pathways. qRT-PCR was used to validate selected lncRNAs in 412 CAD patients and 295 healthy controls. Receiver operating characteristic (ROC) curve analysis was performed to evaluate whether lncRNAs could be used in the diagnosis of CAD patients. Finally, the functional significance of validated lncRNAs was determined in THP-1-derived macrophages. RESULTS: We identified 1210 lncRNAs and 890 mRNAs differentially expressed from the expression profile and validated 7 lncRNAs. Two novel lncRNA biomarkers, ENST00000444488.1 and uc010yfd.1, together with CAD risk factors, had the better performance for discrimination of CAD patients from healthy controls, and ENST00000444488.1 could diagnose acute myocardial infarction (AMI) patients. The knockdown of 20 ENST00000444488.1, uc010yfd.1, ASO3973 and ENST00000602558.1 affected the expression of inflammation-related genes and their nearby genes in THP-1-derived macrophages, respectively. CONCLUSIONS: We offered a transcriptome-wide overview of aberrantly expressed lncRNAs in CAD patients, and identified two novel lncRNA biomarkers for diagnosing CAD. Loss of validated lncRNAs regulated the expression of inflammation-related genes and their nearby genes.

Associations of NADPH oxidase-related genes with blood pressure changes and incident hypertension: The GenSalt Study.

Previous studies have indicated that reactive oxygen species produced by NADPH oxidase (Nox) are important risk factors of hypertension. The current study aims to examine the associations of Nox-related genes with longitudinal blood pressure (BP) changes and the risk of incident hypertension in the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) follow-up study. A total of 1,768 participants from 633 families were included in our analysis. Nine BP measurements were obtained in the morning at baseline and during two follow-up visits. The mixed-effect models were used to investigate the associations of 52 tagged single-nucleotide polymorphisms in 11 Nox-related genes with BP changes and incident hypertension. Gene-based analyses were performed by truncated product method (TPM) and Versatile Gene-based Association Study (VEGAS). Over the 7.2 years of follow-up, systolic BP (SBP) and diastolic BP (DBP) increased, and 32.1% (512) of participants developed hypertension. SNPs rs12094228, rs16861188 and rs12066019 in NCF2 were significantly associated with longitudinal change in SBP (Pinteraction = 1.1 × 10-3, 2.8 × 10-3 and 1.2 × 10-3, respectively). Gene-based analyses revealed that NCF2 was significantly associated with SBP (PTPM = 1.00 × 10-6, PVEGAS = 1.26 × 10-4) and DBP changes (PTPM = 5.84 × 10-4, PVEGAS = 1.04 × 10-3). These findings suggested that NCF2 may play an important role in BP changes over time in the Han Chinese population.

Associations Between Genetic Variants of NADPH Oxidase-Related Genes and Blood Pressure Responses to Dietary Sodium Intervention: The GenSalt Study.

BACKGROUND: The aim of this study was to comprehensively test the associations of genetic variants of nicotinamide adenine dinucleotide phosphate (NADPH) oxidase-related genes with blood pressure (BP) responses to dietary sodium intervention in a Chinese population. METHODS: We conducted a 7-day low-sodium intervention followed by a 7-day high-sodium intervention among 1,906 participants in rural China. BP measurements were obtained at baseline and each dietary intervention using a random-zero sphygmomanometer. Linear mixed-effect models were used to assess the additive associations of 63 tag single-nucleotide polymorphisms in 11 NADPH oxidase-related genes with BP responses to dietary sodium intervention. Gene-based analyses were conducted using the truncated product method. The Bonferroni method was used to adjust for multiple testing in all analyses. RESULTS: Systolic BP (SBP) response to high-sodium intervention significantly decreased with the number of minor T allele of marker rs6967221 in RAC1 (P = 4.51 × 10-4). SBP responses (95% confidence interval) for genotypes CC, CT, and TT were 5.03 (4.71, 5.36), 4.20 (3.54, 4.85), and 0.56 (-1.08, 2.20) mm Hg, respectively, during the high-sodium intervention. Gene-based analyses revealed that RAC1 was significantly associated with SBP response to high-sodium intervention (P = 1.00 × 10-6) and diastolic BP response to low-sodium intervention (P = 9.80 × 10-4). CONCLUSIONS: These findings suggested that genetic variants of NADPH oxidase-related genes may contribute to the variation of BP responses to sodium intervention in Chinese population. Further replication of these findings is warranted.

Associations of Variants in the CACNA1A and CACNA1C Genes With Longitudinal Blood Pressure Changes and Hypertension Incidence: The GenSalt Study.

BACKGROUND: We aimed to examine the associations of voltage-dependent calcium-channel genes CACNA1A and CACNA1C with blood pressure (BP) changes and hypertension incidence in a longitudinal family study. METHODS: A total of 1,768 Han Chinese participants from the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) follow-up study were eligible for the current study. Nine BP measurements were obtained at baseline and each follow-up visit using a random-zero sphygmomanometer. Mixed-effect models were used to assess additive associations of 176 tag single-nucleotide polymorphisms (SNPs) in CACNA1A and CACNA1C with longitudinal BP changes and hypertension incidence. The truncated product method was used for gene-based analysis. The Bonferroni correction was used for adjustment of multiple testing. RESULTS: During an average of 7.2 years of follow-up, 512 (32.1%) participants developed hypertension. CACNA1A SNP rs8182538 was significantly associated with longitudinal diastolic BP (DBP) change after Bonferroni correction ( Pinteraction = 9.90×10 -5 ), with mean DBP increases of 0.85, 1.03, and 1.19mm Hg per year for participants with genotypes C/C , C/T , and T/T , respectively. A similar trend was observed for the association of rs8182538 with systolic BP (SBP) change. In the gene-based analysis, CACNA1A and CACNA1C were significantly associated with DBP change ( P = 2.0×10 -5 ) and SBP change ( P = 1.4×10 -4 ) after Bonferroni correction, respectively. The gene-based associations remained significant after removing rs8182538 within CACNA1A and rs758116 within CACNA1C in sensitivity analysis. CONCLUSIONS: Our findings indicated that CACNA1A and CACNA1C might contribute to BP changes over time in Han Chinese population. Further replication of these findings is warranted.

Caffeine intake and atrial fibrillation incidence: dose response meta-analysis of prospective cohort studies.

BACKGROUND: The association between habitual caffeine intake with incident atrial fibrillation (AF) was unknown. We conducted a meta-analysis to investigate the association between chronic exposure of caffeine and the risk of AF and to evaluate the potential dose-response relation. METHODS: We searched PubMed, EMBASE, and the Cochrane Library up to November 2013 and references of relevant retrieved articles. Prospective cohort studies were included with relative risk (RR) or hazard ratio and 95% confidence intervals (CIs) for AF according to coffee/caffeine intake. RESULTS: Six prospective cohort studies with 228,465 participants were included. In the primary meta-analysis, caffeine exposure was weakly associated with a reduced risk of AF (RR, 0.90; 95% CI, 0.81-1.01; P = 0.07; I(2) = 73%). In subgroup analyses, pooled results from studies with adjustment of potential confounders showed an 11% reduction for low doses (RR, 0.89; 95% CI, 0.80-0.99, P = 0.032; I(2) = 30.9%, P = 0.227) and 16% for high doses (RR, 0.84; 95% CI, 0.75-0.94, P = 0.002; I(2) = 24.1%, P = 0.267) of caffeine consumption in AF risk. An inverse relation was found between habitual caffeine intake and AF risk (P for overall trend = 0.015; P for nonlinearity = 0.27) in dose-response meta-analysis and the incidence of AF decreased by 6% (RR, 0.94; 95% CI, 0.90-0.99) for every 300 mg/d increment in habitual caffeine intake. CONCLUSIONS: It is unlikely that caffeine consumption causes or contributes to AF. Habitual caffeine consumption might reduce AF risk.