Gene-environment Interactions Research Articles

Genotype × Environment Interaction for Grain Yield and Its Component Traits in Wheat (Triticum aestivum L.) for Varietal Recommendations in Meghalaya State of India

The study aims to evaluate the stability of fifteen wheat (Triticum aestivum L.) genotypes under varying sowing dates to identify genotypes with superior grain yield and stability in the North Eastern Region of India. The study also seeks to assess G×E using the Eberhart and Russell model and the AMMI model, to recommend suitable genotypes for cultivation in this region. This is a two-year field study conducted during the rabi seasons of 2017-18 and 2018-19. Fifteen genotypes were sown on six different dates including E1 (27th Oct. 2017-18), E2 (6th Nov. 2017-18), E3 (16th Nov. 2017-18), E4 (27th Oct. 2018-19), E5 (6th Nov. 2018-19), and E6 (16th Nov. 2018-19) to evaluate the stability of these genotypes. This experiment was performed in Randomized Block Design (RBD) with three replications. All genotypes exhibited significant differences across the studied environments. The genotype-environment interaction was significant for most traits except days to 50% crop emergence, test weight, and harvest index. RAJ-3765 and HD-2985 were identified as high-yielding and stable genotypes across all environments, while HD-3118 and HD-2733 performed well in favorable conditions. The AMMI analysis revealed that HD-2985 and RAJ-3765 were the most stable, and WR-544 was the poorest performer. Genotypes RAJ-3765 and HD-2985 showed superior stability and yield across diverse environments, making them suitable for broader cultivation in Meghalaya. HD-2733 and HD-3118 were better suited for favorable environments, while WR-544 was the least adapted. These findings suggest the potential for expanding wheat cultivation in the region using these stable genotypes.

Polygenic Interactions With Environmental Exposures in Blood Pressure Regulation: The HUNT Study.

The essential hypertension phenotype results from an interplay between genetic and environmental factors. The influence of lifestyle exposures such as excess adiposity, alcohol consumption, tobacco use, diet, and activity patterns on blood pressure (BP) is well established. Additionally, polygenic risk scores for BP traits are associated with clinically significant phenotypic variation. However, interactions between genetic and environmental risk factors in hypertension morbidity and mortality are poorly characterized. We used genotype and phenotype data from up to 49 234 participants from the HUNT (Trøndelag Health Study) to model gene-environment interactions between genome-wide polygenic risk scores for systolic BP and diastolic BP and 125 environmental exposures. Among the 125 environmental exposures assessed, 108 and 100 were independently associated with SBP and DBP, respectively. Of these, 12 interactions were identified for genome-wide PRSs for systolic BP and 4 for genome-wide polygenic risk scores for diastolic BP, 2 of which were overlapping (P < 2 × 10-4). We found evidence for gene-dependent influence of lifestyle factors such as cardiorespiratory fitness, dietary patterns, and tobacco exposure, as well as biomarkers such as serum cholesterol, creatinine, and alkaline phosphatase on BP. Individuals that are genetically susceptible to high BP may be more vulnerable to common acquired risk factors for hypertension, but these effects appear to be modifiable. The gene-dependent influence of several common acquired risk factors indicates the potential of genetic data combined with lifestyle assessments in risk stratification, and gene-environment-informed risk modeling in the prevention and management of hypertension.

Adaptability, stability, and productivity of potato breeding clones and cultivars at high latitudes in Europe

The aim of potato breeding is to release cultivars that exhibit high and stable performance across the target population of environments. The objective of this research was therefore to investigate the use of various methods (site regression [SREG], coefficient of variation and regression deviation [σ2δ]) for determining the adaptability and stability of productive and quality traits in the Nordic region of Europe. The multi-environment trials included 256 breeding clones and released cultivars grown by EU farmers at three distinct testing sites over two years in Sweden. There was significant (P < 0.001) variation in tuber yield, starch percentage and reducing sugars in the tuber flesh among the breeding clones and cultivars, testing environments and the genotype by environment interaction (GEI). The environments were very diverse, as revealed by the SREG biplots and particularly for the GEI patterns noted in terms of their productive and quality characteristics. The percentage of stable high-tuber yielding germplasm was greater for breeding clones (23%) than for released European cultivars (2%), thus revealing the advantage of potato breeding in the target population of environments. SLU 1415001 and SLU 1314015 were the most promising breeding clones due to their stable high tuber yield. This characteristic was best for the starch potato cultivars, although none of them exhibited a significant different σ2δ. ‘Talent’ shows an almost stable good performance among low reducing sugar cultivars and breeding clones, which are often unstable in terms of their scoring across environments. Neither a breeding clone nor a cultivar was at the top for stable tuber yield, tuber flesh starch or reducing sugars in the tuber flesh, which shows the challenge faced by potato breeding while addressing the needs of different markets.

Technical considerations for placental tissue processing and the subsequent impact on genome-wide DNA methylation analysis

To assess the impact of postnatal processing on placental DNA methylation, array data from flash-frozen placental tissue was compared to perfluorocarbon-immersed and formalin-fixed paraffin-embedded placental tissue. We observed that tissue exposed to perfluorocarbon showed no significant DNA methylation differences when compared to unprocessed tissue, while formalin processing altered the quality and reliability of the data produced on the DNA methylation array platform. Placental DNA methylation allows for the study of gene–environment interactions that influence the fetal environment and development. Our study highlights that placental post-processing techniques must be considered in the evaluation and interpretation of epigenetic studies.

Genotype by Environment Interaction (GEI) Effect for Potato Tuber Yield and Their Quality Traits in Organic Multi-Environment Domains in Poland

Genotype by Environment Interaction (GEI) Effect for Potato Tuber Yield and Their Quality Traits in Organic Multi-Environment Domains in Poland

High-Dimensional Gene–Environment Interaction Analysis

High-Dimensional Gene–Environment Interaction Analysis

Investigation of the α9-nicotinic receptor single nucleotide polymorphisms induced oncogenic properties and molecular mechanisms in breast cancer.

α9-nAChR, a subtype of nicotinic acetylcholine receptor, is significantly overexpressed in female breast cancer tumor tissues compared to normal tissues. Previous studies have proposed that specific single nucleotide polymorphisms (SNPs) in the CHRNA9 (α9-nAChR) gene are associated with an increased risk of breast cancer in interaction with smoking. The study conducted a breast cancer risk assessment of the α9-nAChR SNP rs10009228 (NM_017581.4:c.1325A > G) in the Taiwanese female population, including 308 breast cancer patients and 198 healthy controls revealed that individuals with the heterozygous A/G or A/A wild genotype have an increased susceptibility to developing breast cancer in the presence of smoking compared to carriers of the G/G variant genotype. Our investigation confirmed the presence of this missense variation, resulting in an alteration of the amino acid sequence from asparagine (N442) to serine (S442) to facilitate phosphorylation within the α9-nAchR protein. Additionally, overexpression of N442 (A/A) in breast cancer cells significantly enhanced cell survival, migration, and cancer stemness compared to S442 (G/G). Four-line triple-negative breast cancer patient-derived xenograft (TNBC-PDX) models with distinct α9-nAChR rs10009228 SNP genotypes (A/A, A/G, G/G) further demonstrated that chronic nicotine exposure accelerated tumor growth through sustained activation of the α9-nAChR downstream oncogenic AKT/ERK/STAT3 pathway, particularly in individuals with the A/G or A/A genotype. Collectively, our study established the links between genetic variations in α9-nAChR and smoking exposure in promoting breast tumor development. This emphasizes the need to consider gene-environment interactions carefully while developing effective breast cancer prevention and treatment strategies.

Decoding the genetic landscape of autism: A comprehensive review

BACKGROUND Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by heterogeneous symptoms and genetic underpinnings. Recent advancements in genetic and epigenetic research have provided insights into the intricate mechanisms contributing to ASD, influencing both diagnosis and therapeutic strategies. AIM To explore the genetic architecture of ASD, elucidate mechanistic insights into genetic mutations, and examine gene-environment interactions. METHODS A comprehensive systematic review was conducted, integrating findings from studies on genetic variations, epigenetic mechanisms (such as DNA methylation and histone modifications), and emerging technologies [including Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9 and single-cell RNA sequencing]. Relevant articles were identified through systematic searches of databases such as PubMed and Google Scholar. RESULTS Genetic studies have identified numerous risk genes and mutations associated with ASD, yet many cases remain unexplained by known factors, suggesting undiscovered genetic components. Mechanistic insights into how these genetic mutations impact neural development and brain connectivity are still evolving. Epigenetic modifications, particularly DNA methylation and non-coding RNAs, also play significant roles in ASD pathogenesis. Emerging technologies like CRISPR-Cas9 and advanced bioinformatics are advancing our understanding by enabling precise genetic editing and analysis of complex genomic data. CONCLUSION Continued research into the genetic and epigenetic underpinnings of ASD is crucial for developing personalized and effective treatments. Collaborative efforts integrating multidisciplinary expertise and international collaborations are essential to address the complexity of ASD and translate genetic discoveries into clinical practice. Addressing unresolved questions and ethical considerations surrounding genetic research will pave the way for improved diagnostic tools and targeted therapies, ultimately enhancing outcomes for individuals affected by ASD.

Genotype by environment interaction effect and fresh root yield stability of cassava genotypes under contrasting nitrogen regimes

Nitrogen (N) is an important nutrient element needed by cassava for optimum yield and it is a vital component of nucleotides (nucleic acids), enzymes, amino acids (proteins), chlorophyll molecules and hormones, among other essential compounds required for growth and development of cassava. Nitrogen stress is a major cassava production constraint, the study aimed to examine genotype by environment interaction (GEI) effects and fresh root yield stability of 203 diverse cassava clones to identify genotypes with stable performance under low and optimum nitrogen regimes across environments using AMMI and GGE biplot analysis. Experiments were conducted using an augmented block design with three replications for two years in three locations in Nigeria. There were significant differences (p < 0.001) in the genotype’s mean performances as well as significant differences (p < 0.001) in the environment’s mean performances for all the traits measured in both nitrogen regimes. The AMMI analysis of variance showed significant effects (p < 0.001) for genotypes, environments and the interactions for fresh root yield in both nitrogen regimes. The biplot analysis showed that for fresh root yield in the optimum nitrogen regime, the principal component accounted for 81.54% of the G + GE (Genotype plus and Genotype by Environment) variation. The G + GE for fresh root yield in the low nitrogen regime accounted for a total of 71.64% of the variation. Ten genotypes were identified as the best genotypes under the optimum nitrogen regime, while eleven genotypes were the best under the low nitrogen regime. Three genotypes under optimum nitrogen regimes were high-yielding. Still, they were unstable in their fresh root yield performance across the environments and can be recommended as specifically adapted to the environments they performed best. Three other genotypes were high-yielding genotypes under low nitrogen but were highly unstable in their fresh root yield mean performance across the environments. The environments Otobi_YR1, Igbariam_YR2, and Umudike_YR1 were identified as the most discriminatory among the test environments. The environments Umudike_YR2 and Igbariam_YR1 were identified as the most representative of the test environments and can represent a mega-environment. The best 21 genotypes that performed above the grand mean for fresh root yield in both nitrogen regimes can be further evaluated on the farmer’s field for possible advancement.

Human milk oligosaccharides are associated with maternal genetics and respiratory health of human milk-fed children

Breastfeeding provides many health benefits, but its impact on respiratory health remains unclear. This study addresses the complex and dynamic nature of the mother-milk-infant triad by investigating maternal genomic factors regulating human milk oligosaccharides (HMOs), and their associations with respiratory health among human milk-fed infants. Nineteen HMOs are quantified from 980 mothers of the CHILD Cohort Study. Genome-wide association studies identify HMO-associated loci on chromosome 19p13.3 and 19q13.33 (lowest P = 2.4e–118), spanning several fucosyltransferase (FUT) genes. We identify novel associations on chromosome 3q27.3 for 6′-sialyllactose (P = 2.2e–9) in the sialyltransferase (ST6GAL1) gene. These, plus additional associations on chromosomes 7q21.32, 7q31.32 and 13q33.3, are replicated in the independent INSPIRE Cohort. Moreover, gene-environment interaction analyses suggest that fucosylated HMOs may modulate overall risk of recurrent wheeze among preschoolers with variable genetic risk scores (P < 0.01). Thus, we report novel genetic factors associated with HMOs, some of which may protect the respiratory health of children.

Evolution, identification, evaluation, and characterization of a stable salinity tolerant sugarcane variety CoG 7

From the fluff generated during 2005, after the preliminary experiments (2005–2007), a promising clone G2005047 has been identified. It showed moderate resistance to red rot (3.6 on a 9-scale scoring system), less susceptibility to shoot borer (13.25%) and internode borers (25.35%), and resistance to woolly aphid (0%). In the Advanced Yield Trials (2008–2011), it showed advantages over check for cane yield (CY) (11.79%), commercial cane sugar percent (CCSP) (0.35%), and sugar yield (SY) (20.33%). To ascertain its large-scale cultivation suitability, it has experimented under adaptive research trials (2012–2014) at farmers’ fields. It exhibited 18.04%, 1.27%, and 19.55% supremacy over the check Co 86032 for CY, CCSP, and SY respectively. The stability of G2005047 under salinity was ascertained through a multi-environment-based experiment (2015–2017). AMMI (Additive Main-effects and Multiplicative Interactions) and GGE (Genotype × Genotype-Environment interaction) biplots were utilized. ANOVA revealed that the genotypic variation exerted the most significant effect followed by genotype × environment interaction and environment. G2005047 had the highest mean values for yield and quality traits with minimal ASV (AMMI stability value) (2.38:CY; 0.57: CCSP; & 0.58:SY) indicating its good-yielding ability and stability. AMMI I, AMMI II, and GGE biplots confirmed the stability of G2005047. In the jaggery quality assessment trials (2018 and 2019), it yielded 37.1% increased jaggery over the check. Also, the clone G2005047, exhibited moderate resistance to red rot disease, less susceptibility to shoot borer (13.25%) and internode borer (25.35%), and resistance against sugarcane woolly aphid (SWA). Due to supremacy for yield, quality, better performance under salinized situations, and tolerance to disease and pests, the clone G2005047 was released as a variety CoG 7 in 2022.

The Environment, Lifestyles and Climate Change: The Many Nongenetic Contributors to The Long and Winding Road to Autoimmune Diseases.

A critical unanswered question is what is causing the increase in the prevalence of autoimmunity and autoimmune diseases around the world. Given the rapidity of change, this is likely the result of major recent alterations in our exposures to environmental risk factors for these diseases. More evidence is becoming available that the evolution of autoimmune disease, years or even decades in the making, results from multiple exposures that alter susceptible genomes and immune systems over time. Exposures during sensitive phases in key developmental or hormonal periods may set the stage for the effects of later exposures. It is likely that synergistic and additive impacts of exposure mixtures result in chronic low-level inflammation. This inflammation may eventually pass thresholds that lead to immune system activation and autoimmunity, and, with further molecular and pathologic changes, the complete clinical syndrome emerges. Much work remains to be done to define the mechanisms and risk and protective factors for autoimmune conditions. However, evidence points to a variety of pollutants, xenobiotics, infections, occupational exposures, medications, smoking, psychosocial stressors, changes in diet, obesity, exercise, and sleep patterns, as well as climate change impacts of increased heat, storms, floods, wildfires, droughts, ultraviolet radiation, malnutrition, and changing infections, as possible contributors. Substantial investments in defining the role of causal factors, in whom and when their effects are most important, the necessary and sufficient gene-environment interactions, improved diagnostics and therapies, and preventative strategies are needed now to limit the many negative personal, societal, and financial impacts that will otherwise occur.

Oxygen-induced stress reveals context-specific gene regulatory effects in human brain organoids.

The interaction between genetic variants and environmental stressors is key to understanding the mechanisms underlying neurological diseases. In this study, we used human brain organoids to explore how varying oxygen levels expose context-dependent gene regulatory effects. By subjecting a genetically diverse panel of 21 brain organoids to hypoxic and hyperoxic conditions, we identified thousands of gene regulatory changes that are undetectable under baseline conditions, with 1,745 trait-associated genes showing regulatory effects only in response to oxygen stress. To capture more nuanced transcriptional patterns, we employed topic modeling, which revealed context-specific gene regulation linked to dynamic cellular processes and environmental responses, offering a deeper understanding of how gene regulation is modulated in the brain. These findings underscore the importance of genotype-environment interactions in genetic studies of neurological disorders and provide new insights into the hidden regulatory mechanisms influenced by environmental factors in the brain.

School of ecological selection of academician of the Russian academy of sciences V.F. Pivovarova

The article outlines the main milestones in the formation of the scientific school of Academician of the Russian Academy of Sciences Viktor Fedorovich Pivovarov – a talented organizer of scientific research on vegetable growing, a leading scientist in the field of ecology, introduction, selection and seed production of vegetable crops, Honored Scientist of the Russian Federation, laureate of the State Prize and Government Prizes of the Russian Federation V. Pivovarov. F. has extensive experience both in Russia and abroad in solving theoretical and practical problems in the industry. He developed a new scientific direction of research on ecological selection and genetics of vegetable crops. The article presents the directions of the ecological selection scientific school: increasing the adaptability of agricultural crops to various environmental factors; identifying the peculiarities of the genotype-environment interaction; development of methods for accelerating the breeding process to create highly productive varieties and hybrids resistant to abiotic and biotic stressors; ecological selection for low levels of radionuclides and technologies that reduce the amount of pollutants in vegetable products. School of V.F. Pivovarov Academician of the Russian Academy of Sciences was organized on the basis of common scientific interests, the importance of environmental research for breeding, a high level of scientific results, continuity and great development prospects.

AMMI and GGE biplot analysis for barley genotype yield performance and stability under multi environment condition in southern Ethiopia

AbstractBarley (Hordeum vulgare L.) is a major grain crop farmed in Ethiopia throughout the long rainy season (Meher) and the short rainy season (Belg) of the year. Barley genotypes were subjected to multi‐environment experiments in six different settings to identify stable genotypes and estimate the impact of genotype × environment interaction (GEI) on grain production. In each area, the field experiment was conducted from mid‐July to January during the primary cropping season of 2021. Three replications of a randomized complete block design were used to set up the trials. According to the additive main effects and multiplicative interaction (AMMI) study, genotype (18.19%), GEI (22.98%), and environment (58.83%) all had an impact on the major treatment sum of squares. The more variance attributed to the environments is a sign of environmental diversity. Given that the two interaction principal component analysis (IPCAs) accounted for 76.94% of the interaction sum of squares, they were sufficient for cross‐validation of the grain yield variance explained by GEI. In contrast to the GGE biplot approaches, which indicated genotypes G12, G3, and G9 as stable and high‐yielding genotypes throughout the environments, the AMMI stability value identified genotypes G3, G12, and G9 as high yielding with stable performance across environments. In general, the GGE biplot and AMMI analysis models demonstrated that genotypes G12, G3, and G9 were stable and yielded well, making G3 acceptable for cultivation in a wider range of environments and G12 and G9 suitable for release.

Pathomechanistic Networks of Motor System Injury in Amyotrophic Lateral Sclerosis.

Amyotrophic Lateral Sclerosis (ALS) is the most common, adult-onset, progressive motor neurodegenerative disorder that results in death within 3 years of the clinical diagnosis. Due to the clinicopathological heterogeneity, any reliable biomarkers for diagnosis or prognosis of ALS have not been identified till date. Moreover, the only three clinically approved treatments are not uniformly effective in slowing the disease progression. Over the last 15 years, there has been a rapid advancement in research on the complex pathomechanistic landscape of ALS that has opened up new avenues for successful clinical translation of targeted therapeutics. Multiple studies suggest that the age-dependent interaction of risk-associated genes with environmental factors and endogenous modifiers is critical to the multi-step process of ALS pathogenesis. In this review, we provide an updated discussion on the dysregulated cross-talk between intracellular homeostasis processes, the unique molecular networks across selectively vulnerable cell types, and the multisystemic nature of ALS pathomechanisms. Importantly, this work highlights the alteration in epigenetic and epitranscriptomic landscape due to gene-environment interactions, which have been largely overlooked in the context of ALS pathology. Finally, we suggest that precision medicine research in ALS will be largely benefitted from the stratification of patient groups based on the clinical phenotype, onset and progression, genome, exposome, and metabolic identities.

Factor-Analytic Variance-Covariance Structures for Prediction Into a Target Population of Environments.

Finlay-Wilkinson regression is a popular method for modeling genotype-environment interaction in plant breeding and crop variety testing. When environment is a random factor, this model may be cast as a factor-analytic variance-covariance structure, implying a regression on random latent environmental variables. This paper reviews such models with a focus on their use in the analysis of multi-environment trials for the purpose of making predictions in a target population of environments. We investigate the implication of random versus fixed effects assumptions, starting from basic analysis-of-variance models, then moving on to factor-analytic models and considering the transition to models involving observable environmental covariates, which promise to provide more accurate and targeted predictions than models with latent environmental variables.

Genetic parameters of milk mid-infrared spectra and their genetic relationships with milk production and feed efficiency traits in French Lacaune dairy sheep

In French dairy sheep, Fourier transform infrared (FTIR) milk spectral data routinely predict the major milk components used in national genetic evaluations. The direct influence of genetic and environmental factors on milk FTIR spectra has been widely studied in dairy cattle, and relatively little in dairy ewes. In this study, 36,873 milk test-day records were available for 4,712 French Lacaune ewes farmed on 8 commercial farms. Our main goals were to provide the first description of spectral data and estimate the genetic parameters of French Lacaune dairy sheep during lactation. Principal component analysis (PCA) results demonstrated the impact of the lactation period on specific wavenumbers, allowing the identification of FTIR spectra collected at early (mo 2-4) and late (mo 5-7) lactation stages. The average estimated heritability (±mean SE) of the FTIR milk spectra from 2,971 to 926 cm-1 (446 wavenumbers) was 0.29 ± 0.02, ranging from 0.13 ± 0.01 to 0.42 ± 0.02. Furthermore, the heritabilities of spectra collected at the beginning or end of lactation changed at each point of the spectrum. However, at each wavenumber, the genomic correlation of transmittance values between these 2 lactation periods was high (>0.77), indicating the absence of a genotype-environment interaction. The genomic correlations between spectral regions and milk production traits (i.e., daily milk yield, fat and protein content, somatic cell score) varied from moderate to high. The results suggested that the most heritable areas of the spectrum were also genetically associated with dairy traits. Finally, the genomic correlations observed between the ewes' feed efficiency traits and the FTIR spectrum were moderate to high, while the genomic correlations between the change in body condition score and spectral data were rather low to moderate. This study confirmed that spectral data from Lacaune ewe milk were heritable, evolved phenotypically and genetically during lactation and were genetically correlated with traits included in breeding goals or traits of interest to the dairy industry.

Refining the scope of genetic influences on alcohol misuse through environmental stratification and gene-environment interaction.

Gene-environment interaction (G × E) is likely an important influence shaping individual differences in alcohol misuse (AM), yet it has not been extensively studied in molecular genetic research. In this study, we use a series of genome-wide gene-environment interaction (GWEIS) and in silico annotation methods with the aim of improving gene identification and biological understanding of AM. We carried out GWEIS for four AM phenotypes in the large UK Biobank sample (N = 360,314), with trauma exposure and socioeconomic status (SES) as moderators of the genetic effects. Exploratory analyses compared stratified genome-wide association (GWAS) and GWEIS modeling approaches. We applied functional annotation, gene- and gene-set enrichment, and polygenic score analyses to interpret the GWEIS results. GWEIS models showed few genetic variants with significant interaction effects across gene-environment pairs. Enrichment analyses identified moderation by SES of the genes NOXA1, DLGAP1, and UBE2L3 on drinking quantity and the gene IFIT1B on drinking frequency. Except for DLGAP1, these genes have not previously been linked to AM. The most robust results (GWEIS interaction p = 4.59e-09) were seen for SES moderating the effects of variants linked to immune-related genes on a pattern of drinking with versus without meals. Our results highlight several genes and a potential mechanism of immune system functioning behind the moderating effect of SES on the genetic influences on AM. Although GWEIS seems to be a preferred approach over stratified GWAS, modeling G × E effects at the molecular level remains a challenge even in large samples. Understanding these effects will require substantial effort and more in-depth phenotypic measurement.

Genome-wide association study for metabolic syndrome reveals APOA5 single nucleotide polymorphisms with multilayered effects in Koreans

Background and purposeGenome-wide association studies (GWAS) of metabolic syndrome (MetS) have predominantly focused on non-Asian populations, with limited representation from East Asian cohorts. Moreover, previous GWAS analyses have primarily emphasized the significance of top single nucleotide polymorphisms (SNPs), poorly explaining other SNP signals in linkage disequilibrium. This study aimed to reveal the interaction between rs651821 and rs2266788, the principal variants of apolipoprotein A5 (APOA5), within the most significant loci identified through GWAS on MetS.MethodsGWAS on MetS and its components was conducted using the data from the Korean Genome and Epidemiology Study (KoGES) city cohort comprising 58,600 individuals with available biochemical, demographic, lifestyle factors, and the most significant APOA5 locus was analyzed further in depth.ResultsAccording to GWAS of MetS and its diagnostic components, a significant association between the APOA5 SNPs rs651821/rs2266788 and MetS/triglycerides/high-density lipoprotein phenotypes was revealed. However, a conditional analysis employing rs651821 unveiled a reversal in the odds ratio for rs2266788. Therefore, rs651821 and rs2266788 emerged as independent and opposing signals in the extended GWAS analysis, i.e., the multilayered effects. Further gene-environment interaction analyses regarding lifestyle factors such as smoking, alcohol consumption, and physical activity underscored these multilayered effects.ConclusionThis study unveils the intricate interplay between rs651821 and rs2266788 derived from MetS GWAS. Removing the influence of lead SNP reveals an independent protective signal associated with rs2266788, suggesting a multilayered effect between these SNPs. These findings underline the need for novel perspectives in future MetS GWAS.