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.
OBJECTIVE: Employing the extended theory of social normative behavior, this study examines the influence of individual and collective norms on COVID-19 vaccination intention across eight Asian countries. We examine how cultural tightness-looseness, defined as the degree of a culture's emphasis on norms and tolerance of deviant behavior, shapes normative social influence on COVID-19 vaccination intention.
METHODS: We conducted a multicountry online survey (N = 2676) of unvaccinated individuals in China, Indonesia, Japan, Malaysia, Singapore, South Korea, Thailand, and Vietnam in May and June 2021, when COVID-19 vaccination mandates had not yet been implemented in those countries. We conducted hierarchical regression analyses with interaction terms for the total sample and then re-categorizied the eight countries as either "tight" (n = 1102) or "loose" (n = 1574) to examine three-way interactions between individual norms, collective norms, and cultural tightness-looseness.
RESULTS: Perceived injunctive norms exerted the strongest impact of all normative factors on vaccination intention. Collective injunctive norms' influence depended on both perceived injunctive and descriptive norms, which was larger when norms were lower (vs. higher). The interactive pattern between perceived and collective norms was more pronounced in countries with greater cultural tightness.
CONCLUSION: Our findings reveal nuanced patterns of how individual and collective social norms influence health behavioral decisions, depending on the degree of cultural tightness-looseness.
METHOD/PROCESS: We study SNS' effects on well-being by accounting for users' personal (i.e., self-disclosure) and situational (i.e., social networks) attributes, using a mixed design of content analysis and social network analysis.
RESULT/CONCLUSION: We compare users' within-person changes in self-disclosure and social networks in two phases (over half a year), drawing on Weibo Depression SuperTalk, an online community for depression, and find: ① Several network attributes strengthen social support, including network connectivity, global efficiency, degree centralization, hubs of communities, and reciprocal interactions. ② Users' self-disclosure attributes reflect positive changes in mental well-being and increased attachment to the community. ③ Correlations exist between users' topological and self-disclosure attributes. ④ A Poisson regression model extracts self-disclosure attributes that may affect users' received social support, including the writing length, number of active days, informal words, adverbs, negative emotion words, biological process words, and first-person singular forms.
INNOVATION: We combine social network analysis with content analysis, highlighting the need to understand SNS' effects on well-being by accounting for users' self-disclosure (content) and communication partners (social networks).
IMPLICATION/CONTRIBUTION: Authentic user data helps to avoid recall bias commonly found in self-reported data. A longitudinal within-person analysis of SNS' effects on well-being is helpful for policymakers in public health intervention, community managers for group organizations, and users in online community engagement.
METHODS/PROCESS: We used a web crawler to obtain a corpus of an online depression community. We introduced a three-stage procedure for metaphor identification in a Chinese Corpus: (1) combine MIPVU to identify metaphorical expressions (ME) bottom-up and formulate preliminary working hypotheses; (2) collect more ME top-down in the corpus by performing semantic domain analysis on identified ME; and (3) analyze ME and categorize conceptual metaphors using a reference list. In this way, we have gained a greater understanding of how depression sufferers conceptualize their experience metaphorically in an under-represented language in the literature (Chinese) of a new genre (online health community).
RESULTS/CONCLUSION: Main conceptual metaphors for depression are classified into PERSONAL LIFE, INTERPERSONAL RELATIONSHIP, TIME, and CYBERCULTURE metaphors. Identifying depression metaphors in the Chinese corpus pinpoints the sociocultural environment people with depression are experiencing: lack of offline support, social stigmatization, and substitutability of offline support with online support. We confirm a number of depression metaphors found in other languages, providing a theoretical basis for researching, identifying, and treating depression in multilingual settings. Our study also identifies new metaphors with source-target connections based on embodied, sociocultural, and idiosyncratic levels. From these three levels, we analyze metaphor research's theoretical and practical implications, finding ways to emphasize its inherent cross-disciplinarity meaningfully.
METHODS: We fine-mapped the classical MHC (chr6: 29.6-33.1 Mb), imputing 216 human leukocyte antigen (HLA) alleles and 4 complement component 4 (C4) haplotypes in studies from the Psychiatric Genomics Consortium Major Depressive Disorder Working Group and the UK Biobank. The total sample size was 45,149 depression cases and 86,698 controls. We tested for association between depression status and imputed MHC variants, applying both a region-wide significance threshold (3.9 × 10-6) and a candidate threshold (1.6 × 10-4).
RESULTS: No HLA alleles or C4 haplotypes were associated with depression at the region-wide threshold. HLA-B*08:01 was associated with modest protection for depression at the candidate threshold for testing in HLA genes in the meta-analysis (odds ratio = 0.98, 95% confidence interval = 0.97-0.99).
CONCLUSIONS: We found no evidence that an increased risk for depression was conferred by HLA alleles, which play a major role in the genetic susceptibility to autoimmune diseases, or C4 haplotypes, which are strongly associated with schizophrenia. These results suggest that any HLA or C4 variants associated with depression either are rare or have very modest effect sizes.
METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors.
RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged.
CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.