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.
METHODS: We conducted a gene-environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I-III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case-control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics.
RESULTS: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P < 1.25 × 10-6) was observed in the meta-analysis (P GxE = 1.2 ×10-6, P Joint = 4.2 ×10-7).
CONCLUSIONS: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans.
IMPACT: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.
METHODS: Data from a 12-country longitudinal SLE cohort, collected prospectively between 2013 and 2020, were analysed. SLE patients with mSACQ defined as the state with serological activity (increased anti-dsDNA and/or hypocomplementemia) but without clinical activity, treated with ≤7.5 mg/day of prednisolone-equivalent GCs and not-considering duration, were studied. The risk of subsequent flare or damage accrual per 1 mg decrease of prednisolone was assessed using Cox proportional hazard models while adjusting for confounders. Observation periods were 2 years and censored if each event occurred.
RESULTS: Data from 1850 mSACQ patients were analysed: 742, 271 and 180 patients experienced overall flare, severe flare and damage accrual, respectively. Tapering GCs by 1 mg/day of prednisolone was not associated with increased risk of overall or severe flare: adjusted HRs 1.02 (95% CI, 0.99 to 1.05) and 0.98 (95% CI, 0.96 to 1.004), respectively. Antimalarial use was associated with decreased flare risk. Tapering GCs was associated with decreased risk of damage accrual (adjusted HR 0.96, 95% CI, 0.93 to 0.99) in the patients whose initial prednisolone dosages were >5 mg/day.
CONCLUSIONS: In mSACQ patients, tapering GCs was not associated with increased flare risk. Antimalarial use was associated with decreased flare risk. Tapering GCs protected mSACQ patients treated with >5 mg/day of prednisolone against damage accrual. These findings suggest that cautious GC tapering is feasible and can reduce GC use in mSACQ patients.
METHODS: This cross-sectional study included 225 adults recruited from 9 East and Southeast Asian countries or regions (Indonesia, Japan, Korea, mainland China, Malaysia, the Philippines, Singapore, Taiwan, and Thailand). Trained interviewers conducted semistructured interviews with 25 participants from the general population of each country/region. Qualitative data were analyzed using a content analysis approach. The selection of items was determined based on interview surveys and team member discussions. The description of items was considered based on a detailed qualitative analysis of the interview survey.
RESULTS: A new region-specific PBM-the Asia PBM 7 dimensions instrument-was designed. It reflects East and Southeast Asian values and comprises 7 items: pain, mental health, energy, mobility, work/school, interpersonal interactions, and burden to others.
CONCLUSIONS: The new region-specific instrument is one of the first PBMs developed in the context of non-Western countries. The Asia PBM 7 dimensions contains 7 items that address the core concepts of health-related quality of life that are deemed important based on East and Southeast Asian health concepts.
METHOD: Cross-sectional study on 68 parents of Malaysian children aged 2-18 years with TSC. QOL was assessed using proxy-report Paediatric Quality of Life Inventory (PedsQL) V.4.0, and scores compared with those from a previous cohort of healthy children. Parents also completed questionnaires on child behaviour (child behaviour checklist (CBCL)) and parenting stress (parenting stress index-short form). Multiple regression analysis was used to determine sociodemographic, medical, parenting stress and behavioural factors that impacted on QOL.
RESULTS: The mean proxy-report PedsQL V.4.0 total scale score, physical health summary score and psychosocial health summary score of the patients were 60.6 (SD 20.11), 65.9 (SD 28.05) and 57.8 (SD 19.48), respectively. Compared with healthy children, TSC patients had significantly lower mean PedsQL V.4.0 total scale, physical health and psychosocial health summary scores (mean difference (95% CI): 24 (18-29), 20 (12-27) and 26 (21-31) respectively). Lower total scale scores were associated with clinically significant CBCL internalising behaviour scores, age 8-18 years and Chinese ethnicity. Lower psychosocial health summary scale scores were associated with clinically significant CBCL internalising behaviour scores, Chinese ethnicity or >1 antiepileptic drug (AED).
CONCLUSION: Parents of children with TSC reported lower PedsQL V.4.0 QOL scores in all domains, with psychosocial health most affected. Older children, those with internalising behaviour problems, of Chinese ethnicity or on >1 AED was at higher risk of lower QOL. Clinicians need to be vigilant of QOL needs among children with TSC particularly with these additional risk factors.
METHODS: Radiation dose received at left outer canthus (LOC) and left eyelid (LE) were measured using Metal-Oxide-Semiconductor Field-Effect Transistor dosimeters on 35 patients who underwent diagnostic or cerebral embolization procedures.
RESULTS: The radiation dose received at the LOC region was significantly higher than the dose received by the LE. The maximum eye lens dose of 1492 mGy was measured at LOC region for an AVM case, followed by 907 mGy for an aneurysm case and 665 mGy for a diagnostic angiography procedure. Strong correlations (shown as R(2)) were observed between kerma-area-product and measured eye doses (LOC: 0.78, LE: 0.68). Lateral and frontal air-kerma showed strong correlations with measured dose at LOC (AKL: 0.93, AKF: 0.78) and a weak correlation with measured dose at LE. A moderate correlation was observed between fluoroscopic time and dose measured at LE and LOC regions.
CONCLUSIONS: The MOSkin dose-monitoring system represents a new tool enabling real-time monitoring of eye lens dose during neuro-interventional procedures. This system can provide interventionalists with information needed to adjust the clinical procedure to control the patient's dose.
KEY POINTS: Real-time patient dose monitoring helps interventionalists to monitor doses. Strong correlation was observed between kerma-area-product and measured eye doses. Radiation dose at left outer canthus was higher than at left eyelid.