THE JEREMIAH METZGER LECTURE: ENVIRONMENTAL INFLUENCES ON COLORECTAL CANCER.

Gene-environmental interactions create risk profiles for sporadic cancer development in patients with colorectal cancer (CRC). For instance, a person's socioeconomic status over their lifetime can affect their level of physical activity and type of diet, and their exposure to tobacco and alcohol may affect their gut microbiome and ultimate risk for developing CRC. Metabolic disease can independently or further change the gut microbiome and alter the typical timing of CRC development, such as is observed and linked with early-onset disease. Patients with microsatellite unstable tumors where DNA mismatch repair is defective have altered immune environments as a result of tumor hypermutability and neoantigen generation, allowing for immune checkpoint inhibitor susceptibility; in such cases, the genetics of the tumor changed the environment. The environment can also change the genetics, where interleukin-6-generated inflammation can inactivate MSH3 protein function that is associated with CRCs which are more metastatic, and patients show poor outcomes. Some specific aspects of the local microbial environment that may be influenced by diet and metabolism are associated with CRC risk, such as Fusobacterium nucleatum infection, and may affect the initiation, perpetuation, and spread of CRC. Overall, both the macro- and microenvironments associated with a person play a major role in CRC formation, progression, and metastases.

Interaction between angiotensin-converting enzyme gene rs4343 polymorphism, environment factors, and angiotensin II level on susceptibility to knee osteoarthritis.

OBJECTIVES: Osteoarthritis (OA) is a complex multifactorial disease. The association of knee OA risk with ACE gene rs4343 polymorphism, gene environment synergistic effect, and angiotensin II serum level has not been previously examined. Therefore, we investigate the ACE gene rs4343 polymorphism in knee OA, and its association with severity of knee OA, and angiotensin II serum level. METHODS: Using a case-control design, we recruited 200 subjects (100 cases and 100 controls) and all were subjected to genotyping of rs4343 SNP by real-time polymerase chain reaction and assay of serum angiotensin II level by ELISA. RESULTS: G containing genotypes (AG and GG) and G allele frequencies of the ACE rs4343 polymorphism were significantly higher in the case group than that in the control group. There was significant association between ACE rs4343 genotypes and risk of knee OA under the following genetic inheritance models: GG vs. AA (P=0.003), AA vs. GG/AG (P=0.014), AG/AA vs. GG (P=0.037), and G vs. A (P<0.001). Stratified analyses showed ACE rs4343 polymorphism was evidently associated with a significantly increased risk of knee OA among those had BMI≥25% (adjusted OR=3.016; 95% CI 1.052-8.648; P=0.040). Additionally, knee OA patients with GG genotype had greater knee specific WOMAC index, Kellgren score, and serum angiotensin II level than those with AA or GA genotypes. CONCLUSION: The investigated polymorphism in the ACE gene rs4343 may reflect the risk and severity of knee OA in the Egyptian population, particularly with the GG genotype. The interaction between ACE gene rs4343 polymorphism and obesity further increased the risk of knee OA. Moreover, the higher angiotensin II level may be involved in the pathogenesis of knee OA.

Systematic discovery of gene-environment interactions underlying the human plasma proteome in UK Biobank.

Understanding how gene-environment interactions (GEIs) influence the circulating proteome could aid in biomarker discovery and validation. The presence of GEIs can be inferred from single nucleotide polymorphisms that associate with phenotypic variability - termed variance quantitative trait loci (vQTLs). Here, vQTL association studies are performed on plasma levels of 1463 proteins in 52,363 UK Biobank participants. A set of 677 independent vQTLs are identified across 568 proteins. They include 67 variants that lack conventional additive main effects on protein levels. Over 1100 GEIs are identified between 101 proteins and 153 environmental exposures. GEI analyses uncover possible mechanisms that explain why 13/67 vQTL-only sites lack corresponding main effects. Additional analyses also highlight how age, sex, epistatic interactions and statistical artefacts may underscore associations between genetic variation and variance heterogeneity. This study establishes the most comprehensive database yet of vQTLs and GEIs for the human proteome.

Genetic and environmental impact on variation in the palatal dimensions in permanent dentition: a twin study.

The objective of this study was to assess the relative contributions of genetic and environmental factors to variation in palatal parameters in twins with completed maxillary growth. The subjects of this study comprised digital dental casts of 50 monozygotic and 35 dizygotic twin pairs. The subjects' average age was 17.95 ± 2.83 years. Zygosity determination was carried out using 15 specific DNA markers and an amel fragment of the amelogenin gene. The interdental distances were measured between selected dental landmarks at the occlusal and gingival planes. The palatal height, surface area and volume were measured between the gingival plane and the midpalate suture. High heritability estimates were observed for all transverse intra-arch measurements. The palate height (a2 = 0.8), dental arch width in the molar area (a2 = 0.86), palatal surface area (a2 = 0.61) and palate volume (a2 = 0.69) were under strong additive genetic control. Moderate genetic dominance was observed for dental arch widths at the gingival line in the canine (d2 = 0.5) and premolar regions (d2 = 0.78-0.81). Sexual dimorphism was shown, with males exhibiting a greater arch width, palate surface area and volume than females (p < 0.01). The majority of palate parameters variation in twins was controlled by genetic effects, and most were highly heritable.

DNA damage and its association with early-life exposome: Gene-environment analysis in Colombian children under five years old.

Environmental exposures and gene-exposure interactions are the major causes of some diseases. Early-life exposome studies are needed to elucidate the role of environmental exposures and their complex interactions with biological mechanisms involved in childhood health. This study aimed to determine the contribution of early-life exposome to DNA damage and the modifying effect of genetic polymorphisms involved in air pollutants metabolism, antioxidant defense, and DNA repair. We conducted a cohort study in 416 Colombian children under five years. Blood samples at baseline were collected to measure DNA damage by the Comet assay and to determine GSTT1, GSTM1, CYP1A1, H2AX, OGG1, and SOD2 genetic polymorphisms. The exposome was estimated using geographic information systems, remote sensing, LUR models, and questionnaires. The association exposome-DNA damage was estimated using the Elastic Net linear regression with log link. Our results suggest that exposure to PM2.5 one year before the blood draw (BBD) (0.83, 95 %CI: 0.76; 0.91), soft drinks consumption (0.94, 0.89; 0.98), and GSTM1 null genotype (0.05, 0.01; 0.36) diminished the DNA damage, whereas exposure to PM2.5 one-week BBD (1.18, 1.06; 1.32), NO2 lag-5 days BBD (1.27, 1.18; 1.36), in-house cockroaches (1.10, 1.00; 1.21) at the recruitment, crowding at home (1.34, 1.08; 1.67) at the recruitment, cereal consumption (1.11, 1.04; 1.19) and H2AX (AG/GG vs. AA) (1.44, 1.11; 1.88) increased the DNA damage. The interactions between H2AX (AG/GG vs. AA) genotypes with crowding and PM2.5 one week BBD, GSTM1 (null vs. present) with humidity at the first year of life, and OGG1 (SC/CC vs. SS) with walkability at the first year of life were significant. The early-life exposome contributes to elucidating the effect of environmental exposures on DNA damage in Colombian children under five years old. The exposome-DNA damage effect appears to be modulated by genetic variants in DNA repair and antioxidant defense enzymes.

A framework for simulating genotype-by-environment interaction using multiplicative models.

KEY MESSAGE: The simulation of genotype-by-environment interaction using multiplicative models provides a general and scalable framework to generate realistic multi-environment datasets and model plant breeding programmes. Plant breeding has been historically shaped by genotype-by-environment interaction (GEI). Despite its importance, however, many current simulations do not adequately capture the complexity of GEI inherent to plant breeding. The framework developed in this paper simulates GEI with desirable structure using multiplicative models. The framework can be used to simulate a hypothetical target population of environments (TPE), from which many different multi-environment trial (MET) datasets can be sampled. Measures of variance explained and expected accuracy are developed to tune the simulation of non-crossover and crossover GEI and quantify the MET-TPE alignment. The framework has been implemented within the R package FieldSimR, and is demonstrated here using two working examples supported by R code. The first example embeds the framework into a linear mixed model to generate MET datasets with low, moderate and high GEI, which are used to compare several popular statistical models applied to plant breeding. The prediction accuracy generally increases as the level of GEI decreases or the number of environments sampled in the MET increases. The second example integrates the framework into a breeding programme simulation to compare genomic and phenotypic selection strategies over time. Genomic selection outperforms phenotypic selection by ∼ 50-70% in the TPE, depending on the level of GEI. These examples demonstrate how the new framework can be used to generate realistic MET datasets and model plant breeding programmes that better reflect the complexity of real-world settings, making it a valuable tool for optimising a wide range of breeding methodologies.

A Systematic Review of the Gene-Lifestyle Interactions on Metabolic Disease-Related Outcomes in Arab Populations.

The increased prevalence of metabolic diseases in the Arab countries is mainly associated with genetic susceptibility, lifestyle behaviours, such as physical inactivity, and an unhealthy diet. The objective of this review was to investigate and summarise the findings of the gene-lifestyle interaction studies on metabolic diseases such as obesity and type 2 diabetes in Arab populations. Relevant articles were retrieved from a literature search on PubMed, Web of Science, and Google Scholar starting at the earliest indexing date through to January 2024. Articles that reported an interaction between gene variants and diet or physical activity were included and excluded if no interaction was investigated or if they were conducted among a non-Arab population. In total, five articles were included in this review. To date, among three out of twenty-two Arab populations, fourteen interactions have been found between the FTO rs9939609, TCF7L2 rs7903146, MC4R rs17782313, and MTHFR rs1801133 polymorphisms and diet or physical activity on obesity and type 2 diabetes outcomes. The majority of the reported gene-diet/ gene-physical activity interactions (twelve) appeared only once in the review. Consequently, replication, comparisons, and generalisation of the findings are limited due to the sample size, study designs, dietary assessment tools, statistical analysis, and genetic heterogeneity of the studied sample.

Factor analytic selection tools and environmental feature-integration enable holistic decision-making in Eucalyptus breeding.

Understanding the genotype-by-environment interaction (GEI) and considering it in the selection process is a sine qua non condition for the expansion of Brazilian eucalyptus silviculture. This study's objective is to select high-performance and stable eucalyptus clones based on a novel selection index that considers the Factor Analytic Selection Tools (FAST) and the clone's reliability. The investigation explores the nuances interplay of GEI and extends its insights by scrutinizing the relationship between latent factors and real environmental features. The analysis, conducted across seven trials in five Brazilian states involving 78 clones, employs FAST. The clonal selection was performed using an extended FAST index weighted by the clone's reliability. Further insights about GEI emerge from the integration of factor loadings with 25 environmental features through a principal component analysis. Ten clones, distinguished by high performance, stability, and reliability, have been selected across the target population of environments. The environmental features most closely associated with factor loadings, encompassing air temperature, radiation, and soil characteristics, emerge as pivotal drivers of GEI within this dataset. This study contributes insights to eucalyptus breeders, equipping them to enhance decision-making by harnessing a holistic understanding-from the genotypes under evaluation to the diverse environments anticipated in commercial plantations.

Assessing genetic and environmental components for pterygium: a nationwide study in Taiwan.

This study aims to estimate the familial risks of pterygium and assess its relative contributions to environmental and genetic factors using the 2000-2017 Taiwan National Health Insurance Research Database. The marginal Cox's model and the polygenic liability model were made. In Taiwan, the prevalence rate of pterygium in 2017 was 1.64% for individuals with affected first-degree relatives, higher than the general population (1.34%). The adjusted relative risk (RR) for pterygium was highest for twins of the same sex (15.54), followed by siblings of the same sex (4.69), offsprings (3.39), siblings of the different sex (2.88), spouse (2.12), parents (1.86), twins of the different sex (1.57), respectively. The phenotypic variance of pterygium was 21.6% from additive genetic variance, 24.3% from common environmental factors shared by family members, and 54.1% from non-shared environmental factors, respectively. Sensitivity analysis by restricting those with surgical pterygium reveals that aRRs and the three components were similar to those of the overall pterygium. In summary, the prevalence rate of pterygium was higher for individuals with affected first-degree relatives than for the general population. The non-shared environmental factors account for half of the phenotypic variance of pterygium; genetic and shared environmental factors explain the rest.

Cracking the type 1 diabetes code: Genes, microbes, immunity, and the early life environment.

Type 1 diabetes (T1D) results from a complex interplay of genetic predisposition, immunological dysregulation, and environmental triggers, that culminate in the destruction of insulin-secreting pancreatic ß cells. This review provides a comprehensive examination of the multiple factors underpinning T1D pathogenesis, to elucidate key mechanisms and potential therapeutic targets. Beginning with an exploration of genetic risk factors, we dissect the roles of human leukocyte antigen (HLA) haplotypes and non-HLA gene variants associated with T1D susceptibility. Mechanistic insights gleaned from the NOD mouse model provide valuable parallels to the human disease, particularly immunological intricacies underlying ß cell-directed autoimmunity. Immunological drivers of T1D pathogenesis are examined, highlighting the pivotal contributions of both effector and regulatory T cells and the multiple functions of B cells and autoantibodies in ß-cell destruction. Furthermore, the impact of environmental risk factors, notably modulation of host immune development by the intestinal microbiome, is examined. Lastly, the review probes human longitudinal studies, unveiling the dynamic interplay between mucosal immunity, systemic antimicrobial antibody responses, and the trajectories of T1D development. Insights garnered from these interconnected factors pave the way for targeted interventions and the identification of biomarkers to enhance T1D management and prevention strategies.

Systemic sclerosis and environment: an intriguing and still debated association.

Systemic sclerosis (SSc) is characterised by a heterogeneous clinical expression probably reflecting the different genetic background of each patient. Progress has been made in the definition of the principal pathogenetic events of the disease that can be summarised in endothelial damage and dysfunction, inflammation with activation of immune system and fibrosis. The aetiology of the disease still remains to be clarified and probably the first events are attributable to the repeated action of environmental stimuli in genetically predisposed subjects.The aim of the present manuscript is to review the most recent and relevant data regarding the association of SSc with environmental factors.

Spatial distribution of residential environment, genetic susceptibility, and psoriasis: A prospective cohort study.

Background: Genetic and environmental factors contribute to psoriasis, but the impact of residential environments on this condition remains uncertain. We aimed to investigate the association of residential environments with psoriasis risk and explore its interaction with genes. Methods: We retrieved data on the spatial distribution of residential environments at 300 and 1000 m buffer zones from the UK Biobank, including the proportions of natural environments, domestic gardens, green spaces, and blue spaces within these zones. We then used Cox hazard models to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between residential environments and psoriasis risk. Lastly, we constructed polygenic risk scores to determine genetic susceptibility and further analyse the interaction with residential environments. Results: Overall, 3755 incident cases of psoriasis were documented during a median follow-up of 12.45 years. Compared with the lowest exposure quantile (Q1), Q4 exposure to natural environments (1000 m buffer: HR = 1.16, 95% CI = 1.05-1.29; 300 m buffer: HR = 1.12, 95% CI = 1.02-1.24) and green spaces (1000 m buffer: HR = 1.16, 95% CI = 1.04-1.28; 300m buffer: HR = 1.10, 95% CI = 1.00-1.21) increased the risk of psoriasis, while Q4 exposure to domestic gardens (1000 m buffer: HR = 0.85, 95% CI = 0.77-0.93; 300m buffer: HR = 0.91, 95% CI = 0.83-1.00) and Q3 exposure to blue spaces (1000 m buffer: HR = 0.89, 95% CI = 0.81-0.98) were negatively associated with psoriasis risk. Among participants with a high genetic risk, those exposed to high levels of natural environments (1000 m buffer: HR = 1.49, 95% CI = 1.15-1.93; 300 m buffer: HR = 1.39, 95% CI = 1.10-1.77) and green spaces (300 m buffer: HR = 1.30, 95% CI = 1.04-1.64) had a higher risk of psoriasis, while those exposed to blue spaces (1000 m buffer: HR = 0.78, 95% CI = 0.63-0.98) had a lower risk of psoriasis. We also observed joint effects of genetic risk and residential environments and an antagonistic additive interaction between blue spaces and genetic risk (P = 0.011). Conclusions: We observed that residing in natural environments and green areas increased the risk of psoriasis in our sample, while proximity to blue spaces and domestic gardens was associated to reduced risks. The association of residential environments with psoriasis risk was modified by genetic susceptibility.

Gene‒Environment Interaction Between CAST Gene and Eye-Rubbing in the Chinese Keratoconus Cohort Study: A Case-Only Study.

Purpose: Keratoconus (KC), characterized by progressive corneal protrusion and thinning, is a complex disease influenced by the combination of genetic and environmental factors. The purpose of this study was to explore potential gene‒environment interaction between the calpastatin (CAST) gene and eye-rubbing in KC. Methods: A case-only study including 930 patients (676 patients with eye-rubbing and 254 patients without eye-rubbing) from the Chinese Keratoconus (CKC) cohort study was performed in the present study. Genotyping of single nucleotide polymorphism (SNP) was conducted using the Illumina Infinium Human Asian Screening Array (ASA) Beadchip. The gene‒environment interactions between CAST gene and eye-rubbing were analyzed using PLINK version 1.90. The interactions between CAST genotypes and eye-rubbing were analyzed by logistic regression models. The SNP-SNP-environment interactions were analyzed using generalized multifactor dimensionality reduction (GMDR). Results: Three SNPs in CAST gene, namely, rs26515, rs27991, and rs9314177, reached the significance threshold for interactions (defined as P < 2.272 × 10-3). Notably, the minor alleles of these three SNPs exhibited negative interactions with eye-rubbing in KC. The results of logistic regression models revealed that the minor allele homozygotes and heterozygotes of rs26515, rs27991, and rs9314177 also exhibited negative interactions with eye-rubbing. Furthermore, GMDR analysis revealed the significant SNP-SNP-environment interactions among rs26515, rs27991, rs9314177, and eye-rubbing in KC. Conclusions: This study identified rs26515, rs27991, and rs9314177 in CAST gene existed gene-environment interactions with eye-rubbing in KC, which is highly important for understanding the underlying biological mechanisms of KC and guiding precision prevention and proper management.

Polycyclic aromatic hydrocarbon and its adducts in peripheral blood: Gene and environment interaction among Chinese population.

BACKGROUND: Benzo(a)pyrene (B[a]P) is the most widely concerned polycyclic aromatic hydrocarbons (PAHs), which metabolizes benzo(a)pyrene-7,8-dihydrodiol-9,10-epoxide (BPDE) in vivo to produce carcinogenic effect on the body. Currently, there is limited research on the role of the variation of metabolic enzymes in this process. METHODS: We carried out a study including 752 participants, measured the concentrations of 16 kinds PAHs in both particle and gaseous phases, urinary PAHs metabolites, leukocyte BPDE-DNA adduct and serum BPDE- Albumin (BPDE-Alb) adduct, and calculated daily intake dose (DID) to assess the cumulative exposure of PAHs. We conducted single nucleotide polymorphism sites (SNPs) of metabolic enzymes, explored the exposure-response relationship between the levels of exposure and BPDE adducts using multiple linear regression models. RESULT: Our results indicated that an interquartile range (IQR) increase in B[a]P, PAHs, BaPeq, 1-hydroxypyrene (1-OHP), 1-hydroxynaphthalene (1-OHNap) and 2-hydroxynaphthalene (2-OHNap) were associated with 26.53 %, 24.24 %, 28.15 %, 39.15 %, 12.85 % and 14.09 % increase in leukocyte BPDE-DNA adduct (all P < 0.05). However, there was no significant correlation between exposure with serum BPDE-Alb adduct (P > 0.05). Besides, we also found the polymorphism of CYP1A1(Gly45Asp), CYP2C9 (Ile359Leu), and UGT1A1(downstream) may affect BPDE adducts level. CONCLUSION: Our results indicated that leukocyte BPDE-DNA adduct could better reflect the exposure to PAHs. Furthermore, the polymorphism of CYP1A1, CYP2C9 and UGT1A1affected the content of BPDE adducts.

LDER-GE estimates phenotypic variance component of gene-environment interactions in human complex traits accurately with GE interaction summary statistics and full LD information.

Gene-environment (GE) interactions are essential in understanding human complex traits. Identifying these interactions is necessary for deciphering the biological basis of such traits. In this study, we review state-of-art methods for estimating the proportion of phenotypic variance explained by genome-wide GE interactions and introduce a novel statistical method Linkage-Disequilibrium Eigenvalue Regression for Gene-Environment interactions (LDER-GE). LDER-GE improves the accuracy of estimating the phenotypic variance component explained by genome-wide GE interactions using large-scale biobank association summary statistics. LDER-GE leverages the complete Linkage Disequilibrium (LD) matrix, as opposed to only the diagonal squared LD matrix utilized by LDSC (Linkage Disequilibrium Score)-based methods. Our extensive simulation studies demonstrate that LDER-GE performs better than LDSC-based approaches by enhancing statistical efficiency by ~23%. This improvement is equivalent to a sample size increase of around 51%. Additionally, LDER-GE effectively controls type-I error rate and produces unbiased results. We conducted an analysis using UK Biobank data, comprising 307 259 unrelated European-Ancestry subjects and 966 766 variants, across 217 environmental covariate-phenotype (E-Y) pairs. LDER-GE identified 34 significant E-Y pairs while LDSC-based method only identified 23 significant E-Y pairs with 22 overlapped with LDER-GE. Furthermore, we employed LDER-GE to estimate the aggregated variance component attributed to multiple GE interactions, leading to an increase in the explained phenotypic variance with GE interactions compared to considering main genetic effects only. Our results suggest the importance of impacts of GE interactions on human complex traits.

Association of Maternal Dietary Habits and Infant MTHFR Gene Polymorphisms with Ventricular Septal Defect in Offspring: A Case-Control Study.

This study aimed to explore the association of maternal diet, infant MTHFR gene polymorphisms, and their interactions with the risk of ventricular septal defects (VSDs). This case-control study recruited 448 mothers of VSD children and 620 mothers of healthy counterparts. Multivariable-adjusted logistic regression models were constructed to examine the association between maternal dietary habits during the first trimester of gestation, MTHFR gene polymorphisms, and VSD. Gene-environment interaction effects were analyzed through logistic regression models, with false discovery rate p-value (FDR_p) < 0.05. Maternal excessive intake of fermented bean curd (OR = 2.00, 95%CI: 1.59-2.52), corned foods (OR = 2.23, 1.76-2.84), fumatory foods (OR = 1.75, 1.37-2.23), grilled foods (OR = 1.34, 1.04-1.72), and fried foods (OR = 1.80, 1.42-2.27) was associated with an increased risk of VSD. Regular intake of fish and shrimp (OR = 0.42, 0.33-0.53), fresh eggs (OR = 0.58, 0.44-0.75), soy products (OR = 0.69, 0.56-0.85), and dairy products (OR = 0.71, 0.59-0.85) was found to reduce the occurrence of VSD. Moreover, MTHFR gene polymorphisms at rs2066470 (homozygous: OR = 4.28, 1.68-10.90), rs1801133 (homozygous: OR = 2.28, 1.39-3.74), and rs1801131 (heterozygous: OR = 1.75, 1.24-2.47; homozygous: OR = 3.45, 1.50-7.95) elevated offspring susceptibility to VSDs. Furthermore, significant interactions of MTHFR polymorphisms with maternal dietary habits were observed, encompassing corned foods, fermented bean curd, fried foods, and grilled foods. Maternal dietary habits; MTHFR polymorphisms at rs2066470, rs1801131, and rs1801133; and their interactions were significantly associated with the occurrence of VSDs in offspring.

Whole-exome sequencing of individuals from an isolated population under extreme conditions implicates rare risk variants of schizophrenia.

Schizophrenia (SCZ), which affects approximately 1% of the world's population, is a global public health concern. It is generally considered that the interplay between genes and the environment is important in the onset and/or development of SCZ. Although several whole-exome sequencing studies have revealed rare risk variants of SCZ, no rare coding variants have been strongly replicated. Assessing isolated populations under extreme conditions might lead to the discovery of variants with a recent origin, which are more likely to have a higher frequency than chance to reflect gene-environment interactions. Following this approach, we examined a unique cohort of Tibetans living at an average altitude above 4500 meters. Whole-exome sequencing of 47 SCZ cases and 53 controls revealed 275 potential novel risk variants and two known variants (12:46244485: A/G and 22:18905934: A/G) associated with SCZ that were found in existing databases. Only one gene (C5orf42) in the gene-based statistics surpassed the exome-wide significance in the cohort. Metascape enrichment analysis suggested that novel risk genes were strongly enriched in pathways relevant to hypoxia, neurodevelopment, and neurotransmission. Additionally, 47 new risk genes were followed up in Han sample of 279 patients with SCZ and 95 controls, only BAI2 variant appearing in one case. Our findings suggest that SCZ patients living at high altitudes may have a unique risk gene signature, which may provide additional information on the underlying biology of SCZ, which can be exploited to identify individuals at greater risk of exposure to hypoxia.

Intrinsic Capacity and Its Biological Basis: A Scoping Review.

BACKGROUND: In 2015, the World Health Organization (WHO) introduced the concept of intrinsic capacity (IC) to define healthy aging based on functional capacity. In this scoping review, we summarized available evidence on the development and validation of IC index scores, the association of IC with health-related factors, and its biological basis. The review specifically focused on identifying current research gaps, proposed strategies to leverage biobank datasets, and opportunities to study the genetic mechanisms and gene-environment interactions underlying IC. METHODS: The literature search was conducted across six databases, including PubMed, CINAHL, Web of Science, Scopus, AgeLine, and PsycINFO, using keywords related to IC. RESULTS: This review included 84 articles, and most of them (n=38) adopted the 5-domains approach to operationalize IC, utilizing correlated five factors or bifactor structures. Intrinsic capacity has consistently shown significant associations with socio-demographic and health-related outcomes, including age, sex, wealth index, nutrition, exercise, smoking, alcohol use, ADL, IADL, frailty, multimorbidity, and mortality. While studies on the biological basis of the composite IC are limited, with only one study finding a significant association with the ApoE gene variants, studies on specific IC domains - locomotor, vitality, cognitive, psychological, and sensory suggest a heritability of 20-85% of IC and several genetic variants associated with these subdomains have been identified. However, evidence on how genetic and environmental factors influence IC is still lacking, with no available study to date. CONCLUSION: Our review found that there was inconsistency in the use of standardized IC measurement tools and indicators, but the IC indices had shown good construct and predictive validity. Research into the genetic and gene-to-environment interactions underlying IC is still lacking, which calls for the use of resources from large biobank datasets in the future.

Genotype by environment interaction and stability analysis for harvest date in sugar beet cultivars.

This research assessed the quantitative and qualitative reactions of commercially grown sugar beets to four different harvest dates and their yield stability. The study followed a split-plot design within a randomized complete block design over 3 years. The main plot involved 10 sugar beet cultivars, while the subplot involved four harvest dates: August 13 (HD1), September 7 (HD2), October 3 (HD3), and November 12 (HD4). The study found that environmental conditions, genotypes, and harvest dates significantly affected various traits of sugar beet. Yearly environmental variations and their interactions with genotypes and harvest dates had substantial impacts on all measured traits at the 1% probability level. Additive main effect and multiplicative interaction analysis based on white sugar yield indicated that genotype and environment's additive effects, as well as the genotype-environment interaction, were significant at 1% probability level. Shokoufa and Arya, which exhibit high white sugar yield (WSY) and low first interaction principal component (IPC1) values, are identified as desirable due to their stability across different environments. Among the harvest dates in different years, the fourth and third dates showed a higher yield than the total average. Perfekta and Ekbatan exhibited high specific adaptability. According to the multi-trait stability index, Arta, Arya and Sina were recognized as stable and superior across all measured traits.

Environmental and Genetic Determinants of Ankylosing Spondylitis.

Exposure to heavy metals and lifestyle factors like smoking contribute to the production of free oxygen radicals. This fact, combined with a lowered total antioxidant status, can induce even more damage in the development of ankylosing spondylitis (AS). Despite the fact that some researchers are looking for more genetic factors underlying AS, most studies focus on polymorphisms within the genes encoding the human leukocyte antigen (HLA) system. The biggest challenge is finding the effective treatment of the disease. Genetic factors and the influence of oxidative stress, mineral metabolism disorders, microbiota, and tobacco smoking seem to be of great importance for the development of AS. The data contained in this review constitute valuable information and encourage the initiation and development of research in this area, showing connections between inflammatory disorders leading to the pathogenesis of AS and selected environmental and genetic factors.