Additive Interaction Research Articles

Estimating Additive Interaction in Two-Stage Individual Participant Data Meta-Analysis.

Individual participant data (IPD) meta-analysis provides important opportunities to study interaction and effect modification for which individual studies often lack power. While previous meta-analyses have commonly focused on multiplicative interaction, additive interaction holds greater relevance for public health and may in certain contexts better reflect biological interaction. Methodological literature on interaction in IPD meta-analysis does not cover additive interaction for models including binary or time-to-event outcomes. We aimed to describe how the Relative Excess Risk due to Interaction (RERI) and other measures of additive interaction or effect modification can be validly estimated within two-stage IPD meta-analysis. First, we explain why direct pooling of study-level RERI estimates may lead to invalid results. Next, we propose a three-step procedure to estimate additive interaction: 1) estimate effects of both exposures and their product term on the outcome within each individual study; 2) pool study-specific estimates using multivariate meta-analysis; 3) estimate an overall RERI and 95% confidence interval based on the pooled effect estimates. We illustrate this procedure by investigating interaction between depression and smoking and risk of smoking-related cancers using data from the PSYchosocial factors and Cancer (PSY-CA) consortium. We discuss implications of this procedure, including the application in meta-analysis based on published data.

The joint associations of physical activity and ultra-processed food consumption with depression: A cohort study in the UK Biobank

BackgroundDespite substantial evidence regarding independent associations between physical activity (PA) and ultra-processed foods (UPF) consumption with depression, the joint effects of these two factors remain unknown. MethodsThis study included 99,126 participants without depression in the UK Biobank at baseline. A 24-h recall method was used to assess UPF consumption, and self-reported total physical activity (TPA), moderate-to-vigorous physical activity (MVPA), and vigorous physical activity (VPA) were assessed by metabolic equivalent task (MET). A series of Cox proportional hazard regression models were used to explore the independent and joint effects of TPA, MVPA, VPA and UPF consumption on depression. ResultsThe incidence rate of depression was 1.94 % [95 % confidence interval (CI): 1.80 %–2.10 %] per 1000 person-years after an average follow-up of 12.10 years. We found that MVPA and UPF consumption had additive interactions on depression risk (p < 0.05). Participants in Q1 of TPA and Q4 of UPF consumption (HR: 1.83, 95%CI: 1.45–2.31) showed a higher risk for depression than those in Q4 of TPA and Q1 of UPF consumption. Compared with the participants with WHO guideline-recommended MVPA and the lowest UPF consumption, those below recommended MVPA (HR: 1.51, 95%CI: 1.20–1.89) or above recommended MVPA (HR: 1.40, 95%CI: 1.10–1.78) and with the highest UPF consumption had a higher risk for depression. LimitationsStudy limitations include use of self-reported data, observational study and concerns regarding generalizability. ConclusionHigher UPF consumption, accompanied by lower PA levels regardless of TPA, MVPA, and VPA, is associated with a higher risk of depression. Our study offers insights on public health priorities to decrease the risk of depression in the population by addressing both PA and UPF consumption together.

Antibacterial efficacy of antimicrobial peptide-functionalized hydrogel particles combined with vancomycin and oxacillin antibiotics

The rise of antibiotic resistant bacteria, such as methicillin-resistant Staphylococcus aureus (MRSA), requires novel approaches to combat infections. Medical devices like implants and wound dressings are frequently used in conjunction with antibiotics, motivating the development of antibacterial biomaterials capable of exhibiting combined antibacterial effects with conventional antibiotics. This study explores the synergistic antibacterial effects of combining antimicrobial peptide (AMP) functionalized hydrogel particles with conventional antibiotics, vancomycin (VCM) and oxacillin (OXA), against Staphylococcus aureus and MRSA. The AMP employed, RRPRPRPRPWWWW-NH2, has previously demonstrated broad-spectrum activity and enhanced stability when attached to hydrogel substrates. Here, checkerboard assays revealed additive and synergistic interactions between the free AMP and both VCM and OXA against Staphylococcus aureus and MRSA. Notably, the AMP-OXA combination displayed a significant synergistic effect against MRSA, with a 512-fold reduction in OXA’s minimum inhibitory concentration (MIC) when combined with free AMP. The observed synergism against MRSA was retained upon covalent AMP immobilization onto the hydrogel particles; however, at a lower rate with a 64-fold reduction in OXA MIC. Despite this, the OXA-AMP hydrogel particle combinations retained considerable synergistic potential against MRSA, a strain resistant to OXA, highlighting the potential of AMP-functionalized materials for enhancing antibiotic efficacy. These findings underscore the importance of developing antimicrobial biomaterials for future medical devices to fight biomaterial-associated infections and reverse antimicrobial resistance.

Associations of ambient air pollution and lifestyle with the risk of NAFLD: a population-based cohort study

BackgroundBoth ambient air pollution and lifestyle factors contribute to the incidence of non-alcoholic fatty liver disease (NAFLD), but previous studies usually focused on single-factor associations. We aimed to assess the joint associations of ambient air pollution and lifestyle with the NAFLD risk and investigate whether lifestyle modifies the association of air pollution with NAFLD risk.MethodsA total of 417,025 participants from the UK Biobank were included in this study. Annual average concentrations of NO2, NOx, PM2.5, PM10, and PM2.5−10 were estimated. A composite lifestyle score was determined based on physical activity, alcohol intake, smoking status, dietary patterns, sedentary time, and sleep duration. Cox proportional hazards regression models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs), as well as the population attributable fraction (PAF). Potential additive interactions of air pollution with lifestyle were also examined by the relative excess risk due to the interaction (RERI) and the attributable proportion due to the interaction (AP).Results4752 (1.14%) incident NAFLD events were recorded. Long-term exposure to air pollutants and an unhealthy lifestyle were significantly associated with the increased risk of incident NAFLD. Lifestyle was the primary factor of incident NAFLD, with a PAF of 37.18% (95% CI: 29.67%, 44.69%). In addition, a significant additive interaction between air pollution and lifestyle for NAFLD risk was observed (RERI: 0.36, 95% CI: 0.09–0.63).ConclusionsLong-term exposure to ambient air pollutants and poor lifestyle were jointly associated with a higher risk of NAFLD.

Grain yield performance of spring maize under different agroecological zones

Maize is an important cereal crop which ranks second in production after rice in Nepal with an increasing demand for livestock and poultry ration but declining in production. This experiment was conducted to screen top- and stable yielding maize hybrids in various agroecological zones of Nepal during the spring season. In this study, nine maize genotypes were evaluated across six environments in randomized complete block design with three replications. The additive main effect and multiplicative interaction (AMMI) ANOVA revealed that environment, genotype, and their interaction had a substantial effect on the grain yield and all five principal components (PCs) were significantly different (P < 0.0001). AMMI stability value revealed that genotypes Rampur composite and Kanchan 101 were the most stable genotypes in all environments. The specific adaptation of genotype as explained by Which-won-where model suggest that Godavari in environment E2, Rajkumar in E4 and E5, and Bisco gold 941 in E1, E3 and E6 were the winning genotypes. Furthermore, the mean-versus-stability model revealed that genotype Kanchan 101 had above average yield with greater stability. In addition, biplot analysis revealed that 78.32% of variation is explained by PC1 and 11.41% by PC2 of the interaction effect. The genotype ranking based on revealed that genotype Kanchan 101 was close to the ideal line and Sano ghogha was at the greatest distance. Conclusively, AMMI and genotype and genotype by environment interaction (GGE) model explicates that genotype Kanchan 101 has both the high yield and stability across all agroecological zones. In future research on multi-year trial with emphasis other agronomic traits to assess the stability and priorities for the development of package of practices for maximizing the grain yield is recommended.

Dietary Carbohydrates, Genetic Susceptibility, and Gout Risk: A Prospective Cohort Study in the UK.

This study aimed to investigate the associations between carbohydrate intake and gout risk, along with interactions between genetic susceptibility and carbohydrates, and the mediating roles of biomarkers. We included 187,387 participants who were free of gout at baseline and completed at least one dietary assessment in the UK Biobank. Cox proportional hazard models were used to estimate the associations between carbohydrate intake and gout risk. Over a median follow-up of 11.69 years, 2548 incident cases of gout were recorded. Total carbohydrate intake was associated with a reduced gout risk (Q4 vs. Q1: HR 0.67, 95% CI 0.60-0.74), as were total sugars (0.89, 0.80-0.99), non-free sugars (0.70, 0.63-0.78), total starch (0.70, 0.63-0.78), refined grain starch (0.85, 0.76-0.95), wholegrain starch (0.73, 0.65-0.82), and fiber (0.72, 0.64-0.80), whereas free sugars (1.15, 1.04-1.28) were associated with an increased risk. Significant additive interactions were found between total carbohydrates and genetic risk, as well as between total starch and genetic risk. Serum urate was identified as a significant mediator in all associations between carbohydrate intake (total, different types, and sources) and gout risk. In conclusion, total carbohydrate and different types and sources of carbohydrate (excluding free sugars) intake were associated with a reduced risk of gout.

Genotype and environmental interactions determine the root digging time and essential oil production in vetiver (Chrysopogon zizanioides (L.) Roberty)

Thirty different vetiver genotypes were grown for evaluation in the experiments at CSIR- Central Institute for Medicinal and Aromatic Plants (CSIR-CIMAP), Lucknow, U.P. 226015, India, to assess the impact of genotype × environment interactions (GEI) on essential oil yield and chemical composition in vetiver lines grown in north India, as well as identifying appropriate genotypes and representative root digging times throughout the year for essential oil production. The interplay of genotype and environment is a significant constraint in crop development. The additive main effects and multiplicative interaction (AMMI) and the analysis of variance (ANOVA) revealed significant effects for genotype (G), environment (E), and genotype × environment (GE) (p < 0.01). The primary root transverse section confirmed the changes in cortical sclerenchyma thickness and variety observed in the dug-out roots from different vetiver genotypes after six and twelve months. The quantity and number of sclerenchyma rows in the peripheral cortical region vary throughout vetiver genotypes. Following root digging, one component (Khusol content) had 40 %, while Khusilal content had 20 % for genotype VTR-23. However, after twelve months, Khusol content had 19 %, whereas Khusilal content had 41 %. The shift in essential oil makeup was apparent. The level of essential oil did not alter considerably. Based on the GGE biplot analysis, VTR-1, 11, and 14 were identified as the most stable genotypes with high essential yields; therefore, it is recommended to use these genotypes in India's enormous agriculture.

The trends of non-accidental mortality burden attributed to compound hot-dry events in China and its provinces in a global warming world

BackgroundGlobal warming has provoked more co-occurrence of hot extreme and dry extreme, namely compound hot-dry events (CHDEs). However, their health impacts have seldom been investigated. This study aimed to characterize CHDEs and assess its mortality burden in China from 1990 to 2100. MethodsCHDEs were defined as a day when daily maximum temperature > its 90th percentile and Standardized Precipitation Index < its 50th percentile. A two-stage approach, including a distributed lag nonlinear model (DLNM) and a multivariate meta-analysis, was used to estimate exposure–response associations of CHDEs with mortality in 358 counties/districts during 2006–2017 in China, which was then applied to assess the national mortality burden attributable to CHDEs from 1990 to 2100. FindingsWe observed a significant increasing trend of CHDEs in China until mid-21st century, and then flatted, while the duration and intensity of CHDEs continuously increased across the 21st century. CHDEs were much riskier (ER=17.82 %, 95 %CI: 14.17 %-21.60 %) than independent hot events (ER=5.86 %,95 %CI: -0.04 %,12.45 %) or dry events (ER=0.07 %,95 %CI: -1.22 %, 1.38 %), and there was significantly additive interaction between hot events and dry events (AP=0.10,95 %CI: 0.04, 0.16). Females (ER=24.28 %, 95 %CI: 19.21 %-29.56 %), the elderly (ER=23.28 %, 95 %CI: 18.23 %-28.55 %), and people living in humid area (ER=18.98 %, 95 %CI: 15.08 %–23.02 %) had higher mortality risks than their counterparts. Mortality burden attributed to CHDEs significantly increased during historical observation and became stable since mid-21st century in China. InterpretationCHDEs would significantly increase mortality with higher risk for females, the elderly and people living in humid areas. Mortality burden has significantly increased during historical observation and will keep relatively steady since mid-21st century.

Joint effects of physical frailty and traditional cardiovascular risk factor control on cardiovascular disease in patients with diabetes

ObjectivesPhysical frailty has been found to increase the risk of multiple adverse outcomes including cardiovascular disease (CVD) in diabetic patients, but whether this could be modified by traditional risk factor control remains unknown. We aimed to explore the joint and interaction effects of frailty and traditional risk factor control on the risk of CVD. DesignA population-based cohort study. Setting and participantsWe included 15,753 participants with type 2 diabetes at baseline from UK Biobank. MeasurementsPhysical frailty was assessed by Fried criteria’s frailty phenotype. The degree of risk factor control was determined by the numbers of the following factors controlled within the target range, including glycated hemoglobin, blood pressure, low-density lipoprotein cholesterol, smoking, and kidney condition. Incident CVD included coronary heart disease, stroke, or heart failure. Cox proportional hazard models were used to assess the individual and joint effects of frailty and risk factor control on the risk of CVD. ResultsAfter a median follow-up of 13.5 years, 1129 incident CVD events were observed. Compared with non-frailty, both prefrailty and frailty were significantly associated with increased risk of CVD (HR 1.22, 95% CI [1.13, 1.31] for pre-frailty and 1.70 [1.53, 1.90] for frailty). For the joint effects, participants with frailty and a low degree of risk factor control (control of 0−1 risk factors) had the highest risk of CVD (2.92 [2.04, 4.17]) compared to those with non-frailty and optimal risk factor control (control of 4−5 risk factors). Moreover, a significant additive interaction between frailty and risk factor control was observed, with around 3.8% of CVD risk attributed to the interactive effects. ConclusionsBoth prefrailty and frailty were associated with a higher risk of CVD in participants with type 2 diabetes. Moreover, physical frailty could interact with the degree of risk factor control in an additive manner to increase the CVD risk.

Agronomic performance and dry matter yield stability of Napier grass (Pennisetum purpureum) genotypes in Southwestern Ethiopia

AbstractThe study aimed to evaluate the yield performance and stability of 10 Napier grass (Pennisetum purpureum) genotypes. A completely randomized design with three replications was used to assess these genotypes. Genotype and genotype × environment (GGE) interaction and additive main effects and multiplicative interactions (AMMI) biplot models were utilized for analysis. The combined results indicated a significant (p ≤ 0.05) impact on dry matter yield and other agronomic traits. Genotypes and environments contributed to 26.93% and 52.17% of the observed variation in dry matter yield, respectively. The GGE and AMMI biplot models identified promising genotypes based on mean dry matter yield and stability. G3, G1, and G10 genotypes were highlighted as stable with high dry matter yield across different environments compared to others, AMMI analysis also revealed that they had above‐average dry matter yield, minimal deviation from the regression line (S2di), and a regression coefficient close to one, which indicated their desirability and stability. Among the 10 genotypes, these Napier grass genotypes were considered the most desirable and stable due to their characteristics. H18 had a longer vector and a small angle with average environmental axis (AEA), making it an ideal environment for selecting superior genotypes accurately. In conclusion, G3 and G1 were identified as ideal genotype candidates for broader utilization under similar environmental conditions.

Prediction of spatial heterogeneity in nutrient-limited sub-tropical maize yield: Implications for precision management in the eastern Indo-Gangetic Plains

Knowledge of the factors influencing nutrient-limited subtropical maize yield and subsequent prediction is crucial for effective nutrient management, maximizing profitability, ensuring food security, and promoting environmental sustainability. We analyzed data from nutrient omission plot trials (NOPTs) conducted in 324 farmers' fields across ten agroecological zones (AEZs) in the Eastern Indo-Gangetic Plains (EIGP) of Bangladesh to explain maize yield variability and identify variables controlling nutrient-limited yields. An additive main effect and multiplicative interaction (AMMI) model was used to explain maize yield variability with nutrient addition. Interpretable machine learning (ML) algorithms in automatic machine learning (AutoML) frameworks were subsequently used to predict attainable yield relative nutrient-limited yield (RY) and to rank variables that control RY. The stack-ensemble model was identified as the best-performing model for predicting RYs of N, P, and Zn. In contrast, deep learning outperformed all base learners for predicting RYK. The best model's square errors (RMSEs) were 0.122, 0.105, 0.123, and 0.104 for RYN, RYP, RYK, and RYZn, respectively. The permutation-based feature importance technique identified soil pH as the most critical variable controlling RYN and RYP. The RYK showed lower in the eastern longitudinal direction. Soil N and Zn were associated with RYZn. The predicted median RY of N, P, K, and Zn, representing average soil fertility, was 0.51, 0.84, 0.87, and 0.97, accounting for 44, 54, 54, and 48% upland dry season crop area of Bangladesh, respectively. Efforts are needed to update databases cataloging variability in land type inundation classes, soil characteristics, and INS and combine them with farmers' crop management information to develop more precise nutrient guidelines for maize in the EIGP.

Plant-based diet indices and their interaction with ambient air pollution on the ovarian cancer survival: A prospective cohort study

BackgroundAmbient air pollution might serve as a prognostic factor for ovarian cancer (OC) survival, yet the relationships between plant-based diet indices (PDIs) and OC survival remain unclear. We aimed to investigate the associations of comprehensive air pollution and PDIs with OC survival and explored the effects of air pollution-diet interactions. MethodsThe present study encompassed 658 patients diagnosed with OC. The overall plant-based diet index (PDI), the healthful PDI (hPDI), and the unhealthful PDI (uPDI) were evaluated by a self-reported validated food frequency questionnaire. In addition, an air pollution score (APS) was formulated by summing the concentrations of particulate matter with a diameter of 2.5 microns or less, ozone, and nitrogen dioxide. Cox proportional hazard models were applied to calculate hazard ratios (HRs) and 95 % confidence intervals (CIs). The potential interactions of APS with PDIs in relation to overall survival (OS) were assessed on both multiplicative and additive scales. ResultsThroughout a median follow-up of 37.60 (interquartile: 24.77–50.70) months, 123 deaths were confirmed. Comparing to the lowest tertiles, highest uPDI was associated with lower OS of OC (HR = 2.06, 95 % CI = 1.30, 3.28; P-trend < 0.01), whereas no significant associations were found between either overall PDI or hPDI and OC survival. Higher APS (HR for per interquartile range = 1.27, 95 % CI = 1.01, 1.60) was significantly associated with worse OC survival, and the association was exacerbated by adherence to uPDI. Notably, an additive interaction was identified between combined air pollution and uPDI (P < 0.005 for high APS and high uPDI). We also found that adherence to overall PDI aggravated associations of air pollution with OC survival (P-interaction = 0.006). ConclusionsJoint exposure to various ambient air pollutants was significantly associated with lower survival among patients with OC, particularly for those who predominantly consumed unhealthy plant-based foods.

Intergenerational transmission of psychopathology across three generations: the role of social support.

Psychopathology runs in families and affects functioning of individuals and their family members. This study assessed the intergenerational transmission of psychopathology risk across three generations, and the extent to which social support factors may protect against this transmission from parents to their offspring. This study was embedded in Generation R, a multi-ethnic population-based cohort from fetal life onwards. Lifetime psychiatric disorders of grandparents were assessed with the Family Informant Schedule Criteria- updated for DSM-IV. Parental psychopathology was repeatedly measured by the Brief Symptom Inventory. Offspring psychopathology (ages 10 and 14) was assessed with the Brief Problem Monitor. Maternal and child social factors were assessed using questionnaire measures and a computerized peer nomination assessment. Our results show that the estimated additive interaction effect for the risk transmission of grandparental and pre- and postnatal parental psychopathology to offspring psychopathology was 23% (95% CI 19; 27). The joint effect of grandparental and parental psychopathology combined with maternal and child social support factors was 13% (95% CI 08; 17)], suggesting that social support factors diminished the intergenerational transmission of psychopathology from (grand)parents (G1 and G2) to offspring (G3). Transmission of psychopathology risk may have long-lasting developmental effects across generations. Social support factors reduced the vulnerability to the effects of psychopathology risk, underscoring the importance of the identification of buffering factors associated with good mental health in adolescents who are at high familial risk.

Optimal formulation of bitter gourd and black galingale extract: Evaluation of effects on inflammation and oxidative stress-related genes

Reactive nitrogen and oxygen species (RNOS) are defined as highly reactive molecules that can be generated endogenously and exogenously. The overproduction of RNOS leads to inflammation, neurodegenerative diseases, diabetes, obesity, and cancer. Natural antioxidants derived from plants are molecules that can neutralize those RNOS. In this study, to increase the antioxidant capacity in neutralizing RNOS, an in vitro evaluation of a binary combination of bitter gourd (Momordica charantia L.) and black galingale (Kaempferia parviflora) extracts as potential natural antioxidant sources at different ratios was conducted. A combination at the ratio of 1:6 showed the highest total phenolic content (TPC) (336.48 ± 0.04 mg GAE/100g DW), while the ratios 1:6 (1511.73 ± 0.20 mg QE/100g DW) and 1:8 (1398.91 ± 0.28 mg QE/100g DW) exhibited the highest total flavonoid content (TFC) compared to the bitter gourd extract and other mixed ratios. The highest scavenging capacities in the DPPH, ABTS, and FRAP assays were detected at the ratios of 1:3 (IC50 9.1 ± 0.07 mg/mL; moderate synergism), 1:6 (IC50 1.07 ± 0.07 mg/mL; synergism), and 1:4 (IC50 2.44 ± 0.04 mg/mL; strong synergism), respectively. Based on the overall cumulative ability to scavenge free radicals with synergistic or additive antioxidant interactions and the presence of functional groups analyzed using FT-IR, the 1:6 ratio was determined as the best combination ratio to neutralize RNOS where 15 proposed beneficial bioactive compounds were detected. Additionally, in vivo studies showed that the increase of CAT mRNA expression and the suppression of NF-kB and CPT-1 mRNA expression at 250 mg/kg BW of dosage confirms that this methanolic mixed extract potentially can effectively act as both an anti-inflammation and antioxidant agent. This study demonstrates that a specific binary combination ratio of plant extracts can synergistically and additively increase their antioxidant capacity, even when utilized in small quantities.

Triglyceride-glycaemic index: Insights into predicting fetal macrosomia and its interaction with gestational diabetes mellitus: A cohort study of Chinese pregnant women.

This study investigates the association between a new insulin resistance indicator, the triglyceride-glucose (TyG) index, and the risk of macrosomia. This is a prospective cohort study. This study included 1332 women who delivered at Peking University International Hospital between October 2017 and August 2019. Participants were divided equally into three groups based on the TyG index. Logistic regression and restricted cubic spline (RCS) analyses were used to evaluate the relationship between the TyG index and macrosomia and conducted subgroup analyses. The TyG index's ability to predict macrosomia was assessed using the receiver operating characteristic (ROC) curve. Multivariable logistic regression analysis revealed that the TyG index is an independent risk factor for macrosomia (Odds ratio [OR] 1.84, 95% confidence interval [CI] 1.02-3.30, p < .05). RCS analysis indicates that the risk of macrosomia increases with the rise of the TyG index (p for nonlinearity <.001) when the TyG index is >6.53. Subgroup analysis showed a synergistic additive interaction between the TyG index and gestational diabetes mellitus (GDM) of macrosomia. The area under the ROC curve for the predictive model was 0.733 (95% CI 0.684, 0.781), with a sensitivity of 76.4% and specificity of 66.9%. Incorporating the TyG index alongside traditional risk factors notably enhances macrosomia prediction (p < .05). The TyG index independently predicts macrosomia, and exhibits an additive interaction with GDM in its occurrence. Integrating the TyG index with traditional risk factors improves the prediction of macrosomia. Clinical trials. gov [NCT02966405].

The interaction between TMEM161B (rs768705) and paranoid personality traits in relation to the risk of major depressive disorder: Results form a longitudinal study of 7642 Chinese freshmen

BackgroundRs768705 (TMEM161B) is one of the identified single nucleotide polymorphisms related to major depressive disorder (MDD). Paranoid personality traits are independently associated with the risk of MDD. This study aimed to investigate the interaction effect between rs768705 (TMEM161B) and paranoid personality traits on the new-onset risk of MDD in Chinese freshmen. MethodsA longitudinal study was conducted among 7642 Chinese freshmen without lifetime MDD at baseline in 2018. 158 new-onset MDD cases were ascertained in 2019. DNA samples were extracted to detect the genotype of rs768705. The diagnostic and statistical manual of mental disorders-IV criteria were used to determine MDD and personality disorder traits. Multiplicative interaction was assessed by logistic regression models. Tomas Andersson's method for calculating biological interactions was used to estimate the additive interaction. ResultsRs768705(AG) (OR = 1.88, 95 % CI: 1.24–2.83) and paranoid personality traits (OR = 3.68, 95 % CI: 2.57–5.26) were significantly associated with the risk of MDD. The multiplicative interaction model with the product term of rs768705 and paranoid personality trait traits had a significant interaction effect (OR = 4.20, 95 % CI:1.62–10.91). There was also a significant additive interaction effect (RR = 7.08, 95 % CI:4.31–11.65) for the incidence of MDD. Seventy seven percent patients among new MDD cases were attributed to the additive interaction effect between rs768705 and paranoid personality traits. ConclusionsRs768705 (AG) may interact with paranoid personality traits to increase the incidence of MDD among Chinese college students. Schools and psychosocial health organizations should pay more attention to individuals with paranoid personality traits for MDD intervention and prevention.

Prevalence of Metabolic Dysfunction-associated Steatotic Liver Disease and Cardiometabolic Risk Factor in US Adolescents.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is widespread worldwide, and a strong link between MASLD and cardiometabolic risk factors (CMRFs) was emphasized. This study characterized the prevalence of MASLD in adolescent population and overlapping CMRFs conditions in MASLD. This is a cross-sectional study of US adolescents aged 12--19 years in the 2017-2020 cycles of the National Health and Nutrition Examination Survey. The relationship between CMRFs and liver steatosis, evaluated by the median controlled attenuation parameter (CAP), was assessed. The prevalence of MASLD in adolescents was 23.77%. Isolated overweight/obesity (35%) was the top CMRF. Non-Hispanic Black patients had the highest proportion of overweight/obesity plus elevated glucose (24%), while non-Hispanic Asian had the highest burden of dyslipidemia (2%, 14%, and 19%). Except hypertension, overweight/obesity (β=48.7; 95% CI, 43.4-54.0), hypertriglyceridemia (β=15.5; 95% CI, 7.2-28.3), low HDL-C (β=10.0; 95% CI, 3.1-16.9), elevated glucose (β=6.9; 95% CI, 0.6-13.2) were all significantly associated with increased CAP values. Increased CAP was linked to the synergistic interactions between overweight/obesity and dyslipidemia or elevated glucose (overweight/obesity and elevated glucose: RERI=8.21, AP=0.45, SI=1.91; overweight/obesity and hypertriglyceridemia: RERI=19.00, AP=0.69, SI=3.53; overweight/obesity and low HDL-C: RERI=10.83, AP=0.58, SI=2.61). Adolescents with combination of overweight/obesity, dyslipidemia (β=15.1; 95% CI, 0.1-30.2) and combination of overweight/obesity, dyslipidemia and elevated glucose (β=48.0; 95% CI, 23.3-72.6) had a significantly higher CAP values. The prevalence of MASLD was alarmingly high in adolescents, and overweight/obesity was the most important CMRF. Overweight/obesity and dyslipidemia or elevated glucose had positive additive interaction effects on liver steatosis.

Interplay between polygenic risk score and solar insolation: Implication for systemic lupus erythematosus diagnosis and pathogenesis

ObjectivesThis research elucidates the correlation between solar radiation insolation, polygenic risk score (PRS), and systemic lupus erythematosus (SLE) diagnosis, utilizing genomic, environmental, and clinical data. MethodsWe included 1,800 SLE participants and 1,800 controls from the Taiwan Precision Medicine Initiative, genotyped via the Affymetrix Genome-Wide TWB 2.0 SNP Array. The study employed a SLE-PRS tailored for individuals of Taiwanese ancestry, comprising 27 single nucleotide polymorphisms (SNPs). QGIS computed solar radiation insolation from participants' residences. We employed logistic regression to investigate the associations between SLE-PRS, solar insolation susceptibility, and SLE. Additive and multiplicative interactions were utilized to assess the interactions between solar insolation and SLE-PRS regarding the risk of SLE. ResultsSLE patients showed decreased solar insolation (p < 0.001). The highest decile of SLE-PRS exhibited a statistically significant lower solar insolation 1, 3, 6, and 12 months prior to diagnosis as compared to the lowest decile. Specifically, there were significant differences observed at 1 and 12 months (p = 0.025 and p = 0.004, respectively). It suggests that higher SLE-PRS correlated with reduced solar insolation tolerance. We observed an increase in SLE risk across ascending SLE-PRS percentiles exclusively in the high solar insolation group, not in the low solar insolation group. However, the interaction effect of SLE-PRS and solar insolation on SLE risk is not statistically significant. Compared to the lowest decile, the highest SLE-PRS decile showed a 10.98-fold increase in SLE risk (95 % CI, 3.773–31.952, p < 0.001). High SLE-PRS scores in conjunction with high solar insolation contribute to SLE incidence. ConclusionsOur study unveils the intertwined nature of UV insolation and polygenic risks in SLE. Future studies should explore the preventative potential of robust solar radiation protection for high-risk individuals before the disease onset.

Genotype-environment interaction for grain yield in maize (Zea mays L.) using the additive main effects and multiplicative interaction (AMMI) model.

Genotype-environment interaction consists of the different response of individual genotypes resulting from changing environmental conditions. Its significance is a phenomenon that makes the breeding process very difficult. On the one hand, the breeder expects stable genotypes, i.e., yielding similarly regardless of environmental conditions. On the other hand, selecting the best genotypes for each region is one of the key challenges for breeders and farmers. The aim of this study was to evaluate genotype-by-environment interaction for grain yield in new maize hybrids developed by Plant Breeding Smolice Co. Ltd., utilizing the additive main effects and multiplicative interaction (AMMI) model. The investigation involved 69 maize (Zea mays L.) hybrids, tested across five locations in a randomized complete block design with three replications. Grain yield varied from 8.76 t ha-1 (SMH_16417 in Smolice) to 16.89 t ha-1 (SMH_16043 in Płaczkowo), with a mean yield of 13.16 t ha-1. AMMI analysis identified significant effects of genotype, environment, and their interaction on grain yield. Analysis of variance indicated that 25.12% of the total variation in grain yield was due to environment factor, 35.20% to genotypic differences, and 21.18% to genotype by environmental interactions. Hybrids SMH_1706 and SMH_1707 are recommended for further breeding programs due to their high stability and superior average grain yield.

Synergistic effect of Metarhizium flavoviride and Serratia marcescens on western flower thrips, Frankliniella occidentalis Pergande (Thysanoptera: Thripidae)

BackgroundThe western flower thrips (WFT), Frankliniella occidentalis Pergande (Thysanoptera: Thripidae), is an important polyphagous pest in both greenhouses and fields. Due to its wide range of host plants and short life cycle, the pest causes overwhelming damage and has led to the destruction of many crops. The combined use of entomopathogenic microorganisms could be an important option to overcome the difficulties in controlling WFT. The virulence of thirty local entomopathogen isolates was tested on WFT, and possibilities of combined application for WFT control were investigated.ResultsAll isolates were virulent for both the second larval stage and the adult stage of WFT. Serratia marcescens Se9 was the most virulent bacterial isolate with a mortality of 54 and 69.6% against the second larval and the adult stages of WFT, respectively. The LC50 values of the Se9 isolate were determined to be 4 × 106 cfu/ml for the second larval stage and 6.3 × 106 cfu/ml for the adult stage. Among the fungal isolates, Metarhizium flavoviride As18 showed a mortality rate of 92.1 and 74.5% against the second larval and the adult stages of WFT, respectively. The LC50 value was determined to be 1.6 × 104 and 7.1 × 104 conidia/ml for the second larval and adult stages of WFT, respectively. The combined application of S. marcescens Se9 and M. flavoviride As18 at different concentrations generally performed better than single treatments, indicating an additive or synergistic interaction. While the single treatment with S. marcescens and M. flavoviride caused a mortality of 20.4 and 49.5%, respectively, the combined application (S. marcescens LC25; M. flavoviride 100 × LC25) resulted in a mortality of 95.7% of the second larval stage. Similarly, the combined application caused 96% mortality in the adult stage, while the single treatments with S. marcescens and M. flavoviride caused 11.3 and 61.3% mortality, respectively.ConclusionThe study showed that the combined application of S. marcescens (LC25) and M. flavoviride (LC25 × 100) resulted in synergism against both second larval and adult stages of WFT. This is the first study to show that the combination of S. marcescens and M. flavoviride had synergistic potential to suppress the WFT population. In future studies, these microorganisms should be formulated together as biopesticides and tested under greenhouse or field conditions.