METHODS: To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74-421 samples).
RESULTS: We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction.
CONCLUSIONS: By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.
SHORT CONCLUSION: In conclusion, INDELs and VNTRs could have important functional consequences in the pathophysiology of obesity, and research on them should be continued to facilitate obesity prediction, prevention, and treatment.
METHODS: We obtained information on medication use and cancer diagnosis from National Health and Nutrition Examination Survey participants. After propensity score matching, we conducted survey-weighted multivariate logistic regression and restricted cubic spline analysis to assess the observed correlation between medication use and cancer while adjusting for multiple covariates. We also performed MR analysis to investigate causality based on summary data from genome-wide association studies on medication use and cancers. We performed sensitivity analyses, replication analysis, genetic correlation analysis, and reverse MR analysis to improve the reliability of MR findings.
RESULTS: We found that the use of agents acting on the renin-angiotensin system was associated with reduced risk of prostate cancer (odds ratio (OR) = 0.42; 95% confidence interval (CI) = 0.27-0.63, P
METHODS: The genotypes were assessed on 144 histologically confirmed NAFLD patients and 198 controls using a Sequenom MassARRAY platform.
RESULTS: The GCKR rs1260326 and rs780094 allele T were associated with susceptibility to NAFLD (OR 1.49, 95 % CI 1.09-2.05, p = 0.012; and OR 1.51, 95 % CI 1.09-2.09, p = 0.013, respectively), non-alcoholic steatohepatitis (NASH) (OR 1.55, 95 % CI 1.10-2.17, p = 0.013; and OR 1.56, 95 % CI 1.10-2.20, p = 0.012, respectively) and NASH with significant fibrosis (OR 1.50, 95 % CI 1.01-2.21, p = 0.044; and OR 1.52, 95 % CI 1.03-2.26, p = 0.038, respectively). Following stratification by ethnicity, significant association was seen in Indian patients between the two SNPs and susceptibility to NAFLD (OR 2.64, 95 % CI 1.28-5.43, p = 0.009; and OR 4.35, 95 % CI 1.93-9.81, p < 0.0001, respectively). The joint effect of GCKR with adiponutrin rs738409 indicated greatly increased the risk of NAFLD (OR 4.14, 95 % CI 1.41-12.18, p = 0.010). Histological data showed significant association of GCKR rs1260326 with high steatosis grade (OR 1.76, 95 % CI 1.08-2.85, p = 0.04).
CONCLUSION: This study suggests that risk allele T of the GCKR rs780094 and rs1260326 is associated with predisposition to NAFLD and NASH with significant fibrosis. The GCKR and PNPLA3 genes interact to result in increased susceptibility to NAFLD.
OBJECTIVES: Our study intended to (i) resolve the taxonomic uncertainties between B. dorsalis and B. carambolae, (ii) reveal the population structure and global invasion routes of B. dorsalis across Asia, Africa, and Oceania, and (iii) identify genomic regions that are responsible for the thermal adaptation of B. dorsalis.
METHODS: Based on a high-quality chromosome-level reference genome assembly, we explored the population relationship using a genome-scale single nucleotide polymorphism dataset generated from the resequencing data of 487 B. dorsalis genomes and 25 B. carambolae genomes. Genome-wide association studies and silencing using RNA interference were used to identify and verify the candidate genes associated with extreme thermal stress.
RESULTS: We showed that B. dorsalis originates from the Southern India region with three independent invasion and spread routes worldwide: (i) from Northern India to Northern Southeast Asia, then to Southern Southeast Asia; (ii) from Northern India to Northern Southeast Asian, then to China and Hawaii; and (iii) from Southern India toward the African mainland, then to Madagascar, which is mainly facilitated by human activities including trade and immigration. Twenty-seven genes were identified by a genome-wide association study to be associated with 11 temperature bioclimatic variables. The Cyp6a9 gene may enhance the thermal adaptation of B. dorsalis and thus boost its invasion, which tended to be upregulated at a hardening temperature of 38 °C. Functional verification using RNA interference silencing against Cyp6a9, led to the specific decrease in Cyp6a9 expression, reducing the survival rate of dsRNA-feeding larvae exposed to extreme thermal stress of 45 °C after heat hardening treatments in B. dorsalis.
CONCLUSION: This study provides insights into the evolutionary history and genetic basis of temperature adaptation in B. dorsalis.
OBJECTIVE: To identify biological pathways that contribute to risk for bipolar disorder (BP) using genes with consistent evidence for association in multiple genome-wide association studies (GWAS).
DATA SOURCES: Four independent data sets with individual genome-wide data available in July 2011 along with all data sets contributed to the Psychiatric Genomics Consortium Bipolar Group by May 2012. A prior meta-analysis was used as a source for brain gene expression data.
STUDY SELECTION: The 4 published GWAS were included in the initial sample. All independent BP data sets providing genome-wide data in the Psychiatric Genomics Consortium were included as a replication sample.
DATA EXTRACTION AND SYNTHESIS: We identified 966 genes that contained 2 or more variants associated with BP at P
Objective: To determine whether subgroups of patients with MDD stratified according to the A/W criterion had a different degree of genetic overlap with obesity-related traits (body mass index [BMI] and levels of C-reactive protein [CRP] and leptin).
Design, Setting, and Patients: This multicenter study assembled genome-wide genotypic and phenotypic measures from 14 data sets of the Psychiatric Genomics Consortium. Data sets were drawn from case-control, cohort, and population-based studies, including 26 628 participants with established psychiatric diagnoses and genome-wide genotype data. Data on BMI were available for 15 237 participants. Data were retrieved and analyzed from September 28, 2015, through May 20, 2017.
Main Outcomes and Measures: Lifetime DSM-IV MDD was diagnosed using structured diagnostic instruments. Patients with MDD were stratified into subgroups according to change in the DSM-IV A/W symptoms as decreased or increased.
Results: Data included 11 837 participants with MDD and 14 791 control individuals, for a total of 26 628 participants (59.1% female and 40.9% male). Among participants with MDD, 5347 (45.2%) were classified in the decreased A/W and 1871 (15.8%) in the increased A/W subgroups. Common genetic variants explained approximately 10% of the heritability in the 2 subgroups. The increased A/W subgroup showed a strong and positive genetic correlation (SE) with BMI (0.53 [0.15]; P = 6.3 × 10-4), whereas the decreased A/W subgroup showed an inverse correlation (-0.28 [0.14]; P = .06). Furthermore, the decreased A/W subgroup had a higher polygenic risk for increased BMI (odds ratio [OR], 1.18; 95% CI, 1.12-1.25; P = 1.6 × 10-10) and levels of CRP (OR, 1.08; 95% CI, 1.02-1.13; P = 7.3 × 10-3) and leptin (OR, 1.09; 95% CI, 1.06-1.12; P = 1.7 × 10-3).
Conclusions and Relevance: The phenotypic associations between atypical depressive symptoms and obesity-related traits may arise from shared pathophysiologic mechanisms in patients with MDD. Development of treatments effectively targeting immunometabolic dysregulations may benefit patients with depression and obesity, both syndromes with important disability.
OBJECTIVE: To investigate the genetics of depression among individuals of East Asian and European descent living in different geographic locations, and with different outcome definitions for depression.
DESIGN, SETTING, AND PARTICIPANTS: Genome-wide association analyses followed by meta-analysis, which included data from 9 cohort and case-control data sets comprising individuals with depression and control individuals of East Asian descent. This study was conducted between January 2019 and May 2021.
EXPOSURES: Associations of genetic variants with depression risk were assessed using generalized linear mixed models and logistic regression. The results were combined across studies using fixed-effects meta-analyses. These were subsequently also meta-analyzed with the largest published GWAS for depression among individuals of European descent. Additional meta-analyses were carried out separately by outcome definition (clinical depression vs symptom-based depression) and region (East Asian countries vs Western countries) for East Asian ancestry cohorts.
MAIN OUTCOMES AND MEASURES: Depression status was defined based on health records and self-report questionnaires.
RESULTS: There were a total of 194 548 study participants (approximate mean age, 51.3 years; 62.8% women). Participants included 15 771 individuals with depression and 178 777 control individuals of East Asian descent. Five novel associations were identified, including 1 in the meta-analysis for broad depression among those of East Asian descent: rs4656484 (β = -0.018, SE = 0.003, P = 4.43x10-8) at 1q24.1. Another locus at 7p21.2 was associated in a meta-analysis restricted to geographically East Asian studies (β = 0.028, SE = 0.005, P = 6.48x10-9 for rs10240457). The lead variants of these 2 novel loci were not associated with depression risk in European ancestry cohorts (β = -0.003, SE = 0.005, P = .53 for rs4656484 and β = -0.005, SE = 0.004, P = .28 for rs10240457). Only 11% of depression loci previously identified in individuals of European descent reached nominal significance levels in the individuals of East Asian descent. The transancestry genetic correlation between cohorts of East Asian and European descent for clinical depression was r = 0.413 (SE = 0.159). Clinical depression risk was negatively genetically correlated with body mass index in individuals of East Asian descent (r = -0.212, SE = 0.084), contrary to findings for individuals of European descent.
CONCLUSIONS AND RELEVANCE: These results support caution against generalizing findings about depression risk factors across populations and highlight the need to increase the ancestral and geographic diversity of samples with consistent phenotyping.
Objectives: To identify novel genome-wide significant loci for PD in Asian individuals and to compare genetic risk between Asian and European cohorts.
Design Setting, and Participants: Genome-wide association data generated from PD cases and controls in an Asian population (ie, Singapore/Malaysia, Hong Kong, Taiwan, mainland China, and South Korea) were collected from January 1, 2016, to December 31, 2018, as part of an ongoing study. Results were combined with inverse variance meta-analysis, and replication of top loci in European and Japanese samples was performed. Discovery samples of 31 575 individuals passing quality control of 35 994 recruited were used, with a greater than 90% participation rate. A replication cohort of 1 926 361 European-ancestry and 3509 Japanese samples was analyzed. Parkinson disease was diagnosed using UK Parkinson's Disease Society Brain Bank Criteria.
Main Outcomes and Measures: Genotypes of common variants, association with disease status, and polygenic risk scores.
Results: Of 31 575 samples identified, 6724 PD cases (mean [SD] age, 64.3 [10] years; age at onset, 58.8 [10.6] years; 3472 [53.2%] men) and 24 851 controls (age, 59.4 [11.4] years; 11 030 [45.0%] men) were analyzed in the discovery study. Eleven genome-wide significant loci were identified; 2 of these loci were novel (SV2C and WBSCR17) and 9 were previously found in Europeans. Replication in European-ancestry and Japanese samples showed robust association for SV2C (rs246814; odds ratio, 1.16; 95% CI, 1.11-1.21; P = 1.17 × 10-10 in meta-analysis of discovery and replication samples) but showed potential genetic heterogeneity at WBSCR17 (rs9638616; I2=67.1%; P = 3.40 × 10-3 for hetereogeneity). Polygenic risk score models including variants at these 11 loci were associated with a significant improvement in area under the curve over the model based on 78 European loci alone (63.1% vs 60.2%; P = 6.81 × 10-12).
Conclusions and Relevance: This study identified 2 apparently novel gene loci and found 9 previously identified European loci to be associated with PD in this large, meta-genome-wide association study in a worldwide population of Asian individuals and reports similarities and differences in genetic risk factors between Asian and European individuals in the risk for PD. These findings may lead to improved stratification of Asian patients and controls based on polygenic risk scores. Our findings have potential academic and clinical importance for risk stratification and precision medicine in Asia.