Genotype-environment interactions and their translational implications

A Population Pharmacokinetic Model to Predict the Individual Starting Dose of Tacrolimus for Tunisian Adults after Renal Transplantation

BACKGROUND

Tacrolimus is the most frequently used immunosuppressive drug for preventing renal rejection. However, its use is hampered by its narrow therapeutic index and large intra and interpatient variability in pharmacokinetics. The objective of this study was to externally validate a tacrolimus population pharmacokinetic model developed for the Dutch population and adjust the model for the Tunisian population for use in predicting the starting dose requirement after kidney transplantation.

METHODS

Data on tacrolimus exposure were obtained from kidney transplant recipients (KTRs) during the first 3 months post-transplantation. External validation of the Dutch model and its adjustment for the Tunisian population was performed using nonlinear mixed-effects modeling.

RESULTS

In total, 1901 whole-blood predose tacrolimus concentrations from 196 adult KTRs were analyzed. According to a visual predictive check, the Dutch model underestimated the starting dose for the Tunisian adult population. The effects of age, together with the CYP3A5*3 and CYP3A4*22 genotypes on tacrolimus clearance were significantly different in the Tunisian population than in the Dutch population. Based on a bodyweight-based dosing, only 21.9% of tacrolimus concentrations were within the target range, whereas this was estimated to be 54.0% with the newly developed model-based dosing. After adjustment, the model was successfully validated internally in a Tunisian population.

CONCLUSIONS

A starting-dose population pharmacokinetic model of tacrolimus for Tunisian KTRs was developed based on a previously published Dutch model. Using this starting dose could potentially increase the percentage of patients achieving target tacrolimus concentrations after the initial starting dose.

Genetic evaluation of heat tolerance in Holsteins using test-day production records and NASA POWER weather data

Heat stress is a prominent issue in livestock production, even for intensively housed dairy herds in Canada. Production records and meteorological data can be combined to assess heat tolerance in dairy cattle. The overall aim of this study was to evaluate the possibility of genetic evaluation for heat tolerance in Canadian dairy cattle. The 2 specific objectives were (1) to estimate the genetic parameters for milk, fat, and protein yield for Holsteins while accounting for high environmental heat loads, and (2) to determine if a genotype-by-environment interaction causes reranking of top-ranked sires between environments with low and high heat loads. A repeatability test-day model with a heat stress function was used to evaluate the genetic merit for milk, fat, and protein yield under heat stress and at thermal comfort for first parity in 5 regions in Canada. The heat stress function for each trait was defined using a specific temperature-humidity index (THI) threshold. The purpose of this function was to quantify the level of heat stress that was experienced by the dairy cattle. The estimated genetic correlation between the general additive genetic effect and the additive effect on the slope of the change in the trait phenotype for milk, fat, and protein yield ranged from -0.16 to -0.30, -0.20 to -0.44, and -0.28 to -0.42, respectively. These negative correlations imply that there is an antagonistic relationship between sensitivity to heat stress and level of production. The heritabilities for milk, fat, and protein yield at 15 units above the THI threshold ranged from 0.15 to 0.27, 0.11 to 0.15, and 0.11 to 0.15, respectively. Finally, the rank correlations between the breeding values from a repeatability model with no heat stress effect and the breeding values accounting for heat stress for the 100 top-ranked bulls indicated possible interaction between milk production traits and THI, resulting in substantial reranking of the top-ranked sires in Canada, especially for milk yield. This is the first study to implement weather data from the NASA POWER database in a genetic evaluation of heat tolerance in dairy cattle. The NASA POWER database is a novel alternative meteorological resource that is potentially more reliable and consistent and with broader coverage than weather station data increasing the number of animals that could be included in a heat stress evaluation.

Evaluating significance of European-associated index SNPs in the East Asian population for 31 complex phenotypes

BACKGROUND

Genome-wide association studies (GWASs) have identified many single-nucleotide polymorphisms (SNPs) associated with complex phenotypes in the European (EUR) population; however, the extent to which EUR-associated SNPs can be generalized to other populations such as East Asian (EAS) is not clear.

RESULTS

By leveraging summary statistics of 31 phenotypes in the EUR and EAS populations, we first evaluated the difference in heritability between the two populations and calculated the trans-ethnic genetic correlation. We observed the heritability estimates of some phenotypes varied substantially across populations and 53.3% of trans-ethnic genetic correlations were significantly smaller than one. Next, we examined whether EUR-associated SNPs of these phenotypes could be identified in EAS using the trans-ethnic false discovery rate method while accounting for winner's curse for SNP effect in EUR and difference of sample sizes in EAS. We found on average 54.5% of EUR-associated SNPs were also significant in EAS. Furthermore, we discovered non-significant SNPs had higher effect heterogeneity, and significant SNPs showed more consistent linkage disequilibrium and allele frequency patterns between the two populations. We also demonstrated non-significant SNPs were more likely to undergo natural selection.

CONCLUSIONS

Our study revealed the extent to which EUR-associated SNPs could be significant in the EAS population and offered deep insights into the similarity and diversity of genetic architectures underlying phenotypes in distinct ancestral groups.

Similarity and diversity of genetic architecture for complex traits between East Asian and European populations

BACKGROUND

Genome-wide association studies have detected a large number of single-nucleotide polymorphisms (SNPs) associated with complex traits in diverse ancestral groups. However, the trans-ethnic similarity and diversity of genetic architecture is not well understood currently.

RESULTS

By leveraging summary statistics of 37 traits from East Asian (N_max=254,373) or European (N_max=693,529) populations, we first evaluated the trans-ethnic genetic correlation (ρ_g) and found substantial evidence of shared genetic overlap underlying these traits between the two populations, with [Formula: see text] ranging from 0.53 (se = 0.11) for adult-onset asthma to 0.98 (se = 0.17) for hemoglobin A1c. However, 88.9% of the genetic correlation estimates were significantly less than one, indicating potential heterogeneity in genetic effect across populations. We next identified common associated SNPs using the conjunction conditional false discovery rate method and observed 21.7% of trait-associated SNPs can be identified simultaneously in both populations. Among these shared associated SNPs, 20.8% showed heterogeneous influence on traits between the two ancestral populations. Moreover, we demonstrated that population-common associated SNPs often exhibited more consistent linkage disequilibrium and allele frequency pattern across ancestral groups compared to population-specific or null ones. We also revealed population-specific associated SNPs were much likely to undergo natural selection compared to population-common associated SNPs.

CONCLUSIONS

Our study provides an in-depth understanding of similarity and diversity regarding genetic architecture for complex traits across diverse populations, and can assist in trans-ethnic association analysis, genetic risk prediction, and causal variant fine mapping.

The impact of genomic variants on patient response to inhaled bronchodilators: a comprehensive update

INTRODUCTION

The bronchodilator response (BDR) depends on many factors, including genetic ones. Numerous single nucleotide polymorphisms (SNPs) influencing BDR have been identified. However, despite several studies in this field, genetic variations are not currently being utilized to support the use of bronchodilators.

AREAS COVERED

In this narrative review, the possible impact of genetic variants on BDR is discussed.

EXPERT OPINION

Pharmacogenetic studies of β₂-agonists have mainly focused on ADRB2 gene. Three SNPs, A46G, C79G, and C491T, have functional significance. However, other uncommon variants may contribute to individual variability in salbutamol response. SNPs haplotypes in ADRB2 may have a role. Many variants in genes coding for muscarinic ACh receptor (mAChR) have been reported, particularly in the M₂ and, to a lesser degree, M₃ mAChRs, but no consistent evidence for a pharmacological relevance of these SNPs has been reported. Moreover, there is a link between SNPs and ethnic and/or age profiles regarding BDR. Nevertheless, replication of pharmacogenetic results is limited and often, BDR is dissociated from what is expected based on SNP identification. Pharmacogenetic studies on bronchodilators must continue. However, they must integrate data derived from a multi-omics approach with epigenetic factors that may modify BDR.

Neural crest E-cadherin loss drives cleft lip/palate by epigenetic modulation via pro-inflammatory gene-environment interaction

Gene-environment interactions are believed to play a role in multifactorial phenotypes, although poorly described mechanistically. Cleft lip/palate (CLP), the most common craniofacial malformation, has been associated with both genetic and environmental factors, with little gene-environment interaction experimentally demonstrated. Here, we study CLP families harbouring CDH1/E-Cadherin variants with incomplete penetrance and we explore the association of pro-inflammatory conditions to CLP. By studying neural crest (NC) from mouse, Xenopus and humans, we show that CLP can be explained by a 2-hit model, where NC migration is impaired by a combination of genetic (CDH1 loss-of-function) and environmental (pro-inflammatory activation) factors, leading to CLP. Finally, using in vivo targeted methylation assays, we demonstrate that CDH1 hypermethylation is the major target of the pro-inflammatory response, and a direct regulator of E-cadherin levels and NC migration. These results unveil a gene-environment interaction during craniofacial development and provide a 2-hit mechanism to explain cleft lip/palate aetiology.

Modeling the influence of phenotypic plasticity on maize hybrid performance

Phenotypic plasticity, the ability of an individual to alter its phenotype in response to changes in the environment, has been proposed as a target for breeding crop varieties with high environmental fitness. Here, we used phenotypic and genotypic data from multiple maize (Zea mays L.) populations to mathematically model phenotypic plasticity in response to the environment (PPRE) in inbred and hybrid lines. PPRE can be simply described by a linear model in which the two main parameters, intercept a and slope b, reflect two classes of genes responsive to endogenous (class A) and exogenous (class B) signals that coordinate plant development. Together, class A and class B genes contribute to the phenotypic plasticity of an individual in response to the environment. We also made connections between phenotypic plasticity and hybrid performance or general combining ability (GCA) of yield using 30 F₁ hybrid populations generated by crossing the same maternal line with 30 paternal lines from different maize heterotic groups. We show that the parameters a and b from two given parental lines must be concordant to reach an ideal GCA of F₁ yield. We hypothesize that coordinated regulation of the two classes of genes in the F₁ hybrid genome is the basis for high GCA. Based on this theory, we built a series of predictive models to evaluate GCA in silico between parental lines of different heterotic groups.

Heterogeneity Assessment of Kenaf Breeding Field through Spatial Dependence Analysis on Crop Growth Status Map Derived by Unmanned Aerial Vehicle

The investigation of quantitative phenotypic traits resulting from the interaction between targeted genotypic traits and environmental factors is essential for breeding selection. Therefore, plot-wise controlled environmental factors must be invariable for accurate identification of phenotypes. However, the assumption of homogeneous variables within the open-field is not always accepted, and requires a spatial dependence analysis to determine whether site-specific environmental factors exist. In this study, spatial dependence within the kenaf breeding field was assessed in a geo-tagged height map derived from an unmanned aerial vehicle (UAV). Local indicators of spatial autocorrelation (LISA) were applied to the height map using Geoda software, and the LISA map was generated in order to recognize the existence of kenaf height status clusters. The spatial dependence of the breeding field used in this study appeared in a specific region. The cluster pattern was similar to the terrain elevation pattern of this field and highly correlated with drainage capacity. The cluster pattern could be utilized to design random blocks based on regions that have similar spatial dependence. We confirmed the potential of spatial dependence analysis on a crop growth status map, derived by UAV, for breeding strategy design with a tight budget.

Current State of Modeling Human Psychiatric Disorders Using Zebrafish

Psychiatric disorders are highly prevalent brain pathologies that represent an urgent, unmet biomedical problem. Since reliable clinical diagnoses are essential for the treatment of psychiatric disorders, their animal models with robust, relevant behavioral and physiological endpoints become necessary. Zebrafish (Danio rerio) display well-defined, complex behaviors in major neurobehavioral domains which are evolutionarily conserved and strikingly parallel to those seen in rodents and humans. Although zebrafish are increasingly often used to model psychiatric disorders, there are also multiple challenges with such models as well. The field may therefore benefit from a balanced, disease-oriented discussion that considers the clinical prevalence, the pathological complexity, and societal importance of the disorders in question, and the extent of its detalization in zebrafish central nervous system (CNS) studies. Here, we critically discuss the use of zebrafish for modeling human psychiatric disorders in general, and highlight the topics for further in-depth consideration, in order to foster and (re)focus translational biological neuroscience research utilizing zebrafish. Recent developments in molecular biology research utilizing this model species have also been summarized here, collectively calling for a wider use of zebrafish in translational CNS disease modeling.

PhenoBot: an automated system for leaf area analysis using deep learning

A low-cost dynamic image capturing and analysis pipeline using color-based deep learning segmentation was developed for direct leaf area estimation of multiple crop types in a commercial environment. Crop yield is largely driven by intercepted radiation of the leaf canopy, making the leaf area index (LAI) a critical parameter for estimating yields. The growth rate of leaves at different growth stages determines the overall LAI, which is used by crop growth models (CGM) for simulating yield. Consequently, precise phenotyping of the leaves can help elucidate phenological processes relating to resource capturing. A stable system for acquiring images and a strong data processing backend play a vital role in reducing throughput time and increasing accuracy of calculations, compared to manual analysis. However, most available solutions are not dynamic, as they use color-based segmentation, which fails to capture leaves with varying shades and shapes. We have developed a system that uses a low-cost setup to acquire images and an automated pipeline to manage the data storage on the device and in the cloud. The system is powered by virtual machines that run multiple custom-trained deep learning models to segment out leaves, calculate leaf area (LA) for the whole set and at the individual leaf level, overlays important information on the images, and appends them on a compatible file used for CGMs with very high accuracy. The pipeline is dynamic and can be used for multiple crops. The use of open-source hardware, platforms, and algorithms makes this system affordable and reproducible.

Detecting associated genes for complex traits shared across East Asian and European populations under the framework of composite null hypothesis testing

Background

Detecting trans-ethnic common associated genetic loci can offer important insights into shared genetic components underlying complex diseases/traits across diverse continental populations. However, effective statistical methods for such a goal are currently lacking.

Methods

By leveraging summary statistics available from global-scale genome-wide association studies, we herein proposed a novel genetic overlap detection method called CONTO (COmposite Null hypothesis test for Trans-ethnic genetic Overlap) from the perspective of high-dimensional composite null hypothesis testing. Unlike previous studies which generally analyzed individual genetic variants, CONTO is a gene-centric method which focuses on a set of genetic variants located within a gene simultaneously and assesses their joint significance with the trait of interest. By borrowing the similar principle of joint significance test (JST), CONTO takes the maximum P value of multiple associations as the significance measurement.

Results

Compared to JST which is often overly conservative, CONTO is improved in two aspects, including the construction of three-component mixture null distribution and the adjustment of trans-ethnic genetic correlation. Consequently, CONTO corrects the conservativeness of JST with well-calibrated P values and is much more powerful validated by extensive simulation studies. We applied CONTO to discover common associated genes for 31 complex diseases/traits between the East Asian and European populations, and identified many shared trait-associated genes that had otherwise been missed by JST. We further revealed that population-common genes were generally more evolutionarily conserved than population-specific or null ones.

Conclusion

Overall, CONTO represents a powerful method for detecting common associated genes across diverse ancestral groups; our results provide important implications on the transferability of GWAS discoveries in one population to others.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03637-8.

On the causal interpretation of heritability from a structural causal modeling perspective

Heritability estimated using the analysis of variance (ANOVA) for ascribing causal responsibility to genes for a phenotype has been criticized widely. First, there are problems associated with articulating the exact causal meaning of heritability in the standard model. Second, in conditions of gene-environment interaction or covariation that violate the assumptions made by the standard model, a causal interpretation of heritability is thought to be unwarranted. This paper aims to rethink these ideas and associated disputes from a structural causal modeling (SCM) perspective. Using SCM, we show that, in the standard model, heritability reflects the causal effect of eliminating genotypic differences on the change of phenotypic variance of a population. In the presence of interaction or covariation, heritability is estimated incorrectly using ANOVA. However, SCM can provide the causal effect of genotypes on the phenotypic variance regarding particular interventions. We also show that SCM can identify different types of causal effect and answer individual-level causal questions. We conclude that SCM has the resources to provide a systematic causal interpretation that can supplement traditional heritability estimates via ANOVA and offer a more substantial causal analysis of genetic causation.

Flavor and Other Quality Traits of Tomato Cultivars Bred for Diverse Production Systems as Revealed in Organic Low-Input Management

This study was conducted to determine the volatile organic compounds (VOCs) associated with fruit flavor in diverse tomato cultivars (salad and cocktail cultivars) under organic low-input production. For this objective, 60 cultivars deriving from very diverse breeding programs 1880-2015 were evaluated in 2015, and a subset of 20 cultivars was selected for further evaluation in 2016. The diversity of instrumentally determined traits, especially for VOCs concentration and sensory properties (fruit firmness, juiciness, skin firmness, sweetness, sourness, aroma, and acceptability), was investigated at two harvest dates. The evaluation of the cultivars exhibited a wide range of variation for all studied traits, with the exception of a few VOCs. Cultivar had the most important effect on all instrumentally determined traits, while the influence of cultivar × harvest date × year interaction was significant for 17 VOCs, but not for total soluble solid (TSS) and titratable acidity (TA). The VOCs with the highest proportion (>8%) were hexanal, 6-methyl-5-heptene-2-one, 2-isobutylthiazole, and (E)-2-hexenal, which were identified in all cultivars. Twelve VOCs significantly correlated with one or more sensory attributes and these VOCs also allowed differentiation of the fruit type. Among these VOCs, phenylethyl alcohol and benzyl alcohol positively correlated with acceptability in the cocktail cultivars, whereas 2-isobuthylthiazole and 6-methyl-5-hepten-2-ol negatively correlated with acceptability in the salad cultivars. As a result of this study, organic breeders are recommended to use cultivars from a wide range of breeding programs to improve important quality and agronomic traits. As examples, salad tomatoes "Campari F1", "Green Zebra", and "Auriga", as well as cocktail tomatoes "Supersweet 100 F1", "Sakura F1", and "Black Cherry" showed higher scores for the sensory attributes aroma and acceptability under organic low-input growing conditions. It remains a challenge for breeders and growers to reduce the trade-off of yield and quality.

QTL Mapping for Haploid Inducibility Using Genotyping by Sequencing in Maize

Doubled haploid (DH) technology in maize takes advantage of in vivo haploid induction (HI) triggered by pollination of donors of interest with inducer genotypes. However, the ability of different donors to be induced-inducibility (IND), varies among germplasm and the underlying molecular mechanisms are still unclear. In this study, the phenotypic variation for IND in a mapping population of temperate inbred lines was evaluated to identify regions in the maize genome associated with IND. A total of 247 F_2:3 families derived from a biparental cross of two elite inbred lines, A427 and CR1Ht, were grown in three different locations and Inclusive Composite Interval Mapping (ICIM) was used to identify quantitative trait loci (QTL) for IND. In total, four QTL were detected, explaining 37.4% of the phenotypic variance. No stable QTL was found across locations. The joint analysis revealed QTL × location interactions, suggesting minor QTL control IND, which are affected by the environment.

Maternal Nutrition and Meat Quality of Progeny

The concept of fetal programming is based on the idea that nutritional status and environmental conditions encountered by the dam during pregnancy can have lifetime impacts on her offspring. These changes in the gestational environment have been shown to influence fetal development and subsequent growth performance, carcass composition, and meat quality characteristics. Beef fetuses can be particularly prone to experiencing variations in the maternal environment during development owing to a relatively long duration of pregnancy potentially exposing the dam to environmental temperature stress and/or seasonal conditions that can compromise feed quality or quantity. If feed is limited or forage conditions are poor, a maternal deficiency in protein and/or energy can occur as well as fluctuations in body condition of the dam. As a result, the fetus may receive inadequate levels of nutrients, potentially altering fetal development. There are critical windows of development during each stage of gestation in which various tissues, organs, and metabolic systems may be impacted. Skeletal muscle and adipose tissue are particularly vulnerable to alterations in the gestational environment because of their low priority for nutrients relative to vital organs and systems during development. The timing and severity of the environmental event or stressor as well as the ability of the dam to buffer negative effects to the fetus will dictate the developmental response. Much of the current research is focused on the influence of specific nutrients and timing of nutritional treatments on offspring carcass composition and meat quality, with the goal of informing strategies that will ultimately allow for the use of maternal nutritional management as a tool to optimize performance and meat quality of offspring.

AMMI and GGE biplot analysis for yield performance and stability assessment of selected Bambara groundnut (Vigna subterranea L. Verdc.) genotypes under the multi-environmental trails (METs)

The stability and high yielding of Vigna subterranea L. Verdc. genotype is an important factor for long-term development and food security. The effects of G × E interaction on yield stability in 30 Bambara groundnut genotypes in four different Malaysian environments were investigated in this research. The experiment used a randomized complete block design with three replications in each environment. Over multiple harvests, yield component traits such as the total number of pods per plant, fresh pods weight (g), hundred seeds weight (g), and yield per hectare were evaluated in the main and off-season in 2020 and 2021. Stability tests for multivariate stability parameters were performed based on analyses of variance. For all the traits, the pooled analysis of variance revealed highly significant (p < 0.01) variations between genotypes, locations, seasons, and genotypes by environment (G × E interaction). A two-dimensional GGE biplot was generated using the first two principal components (axis 1 and axis 2), which accounted for 94.97% and 3.11% difference in GEI for yield per hectare, respectively. Season and location were found to be the most significant causes of yield heterogeneity, accounting for 31.13% and 14.02% of overall G + E + G × E variation, respectively, according to the combined study of variance. The GGE biplot revealed that the three winning genotypes G1, G3, and G5 appear across environments whereas AMMI model exposed genotypes viz G18, G14, G7, G3, G1, and G5 as best performer. Based on ideal genotype ranking genotype G1 was the best performer, with a high mean yield and high stability in the tested environment. According to the AEC line, genotypes G1 and G3 were extremely stable, while genotypes G2 and G4 were low stable, with a high average yielding per hectare. A GGE and AMMI biplot graphically showed the interrelationships between the tested environment and genotypes, classified genotypes into three categories as well as simplifying visual evaluations, according to this investigation. According to our results, breeding could improve yield production, and the genotypes discovered could be recommended for commercial cultivation.

Morphological Description and Ethnobotanical Review of the Orphan Crop Myin-Hkwa (Centella asiatica L.) From Myanmar

Centella asiatica is a medicinal herb commonly known as Asiatic pennywort or gotu kola. The species is valued for its medicinal and nutritional properties. It is a perennial plant with leaves and stems that can be consumed as a green leafy vegetable. It is used as a folk remedy to cure various mild and chronic diseases due to its anti-rheumatic, antipyretic, antibacterial, antiviral, and anti-inflammatory effects, and as a mental rejuvenator. Although the species is widely distributed throughout the tropics and subtropics, its recognition was limited. The morphological description of C. asiatica is not well-documented in Myanmar, in Burmese or other local languages. Plant assessment via morphological markers is one of the ultimate methods for the primary description and characterization of their phenotypic traits. The objectives of this study were focused on the description of Myanmarese C. asiatica grown in Japan through morphological markers and a brief overview of its ethnobotanical use in Asia. Morphological characterization revealed the quantitative and qualitative differences regarding several traits among assessed C. asiatica samples. Furthermore, the study can provide information on the primary C. asiatica cultivation system in Japan, as it can be a potentially new and economically important crop for the Japanese market.

Two novel microRNAs and their association with absolute blood pressure parameters in an urban South African community

MicroRNAs are important in development of disease, and description of novel microRNAs adds to the pool of microRNAs that can be targeted for diagnostic and therapeutic purposes in disease. Herein, we aimed to describe novel microRNAs in a normotensive and hypertensive African population and relate their expression to blood pressure parameters and hypertension status. Previous work using next-generation sequencing showed differential expression of two novel microRNAs in the blood of normotensives and hypertensives. Herein, we have investigated these novel microRNAs by quantitative reverse transcription polymerase chain reaction in a cohort of 881 participants in this study. The relationship between the novel microRNAs and systolic and diastolic blood pressure as well as mean arterial pressure was also investigated. Age and sex-adjusted Spearman’s correlations were used to assess the relationship between microRNAs and cardiovascular risk profile variables whilst multivariable logistic regression models were used to assess the association of microRNAs with screen-detected and known hypertension. The novel microRNAs (miR-novel-chr1_36178 and miR-novel-chr15_18383) were significantly dysregulated by hypertension status. The expression of miR-novel-chr1_36178 differed according to sex, correlated with mean arterial pressure and systolic and diastolic blood pressure at higher levels of expression and was associated with screen-detected hypertension. The association of miR-novel-chr1_36178 expression with mean arterial pressure and systolic and diastolic blood pressure, as well as its dysregulation according to hypertension status suggests its possible utility as a biomarker target for hypertension diagnosis and/or therapeutics. Furthermore, its association with screen detected hypertension and dose-response relationship with blood pressure suggests it may be used to identify and monitor individuals at risk of hypertension.

Expression of DLX6 Gene in Mandibular Deficiency (Retrognathic Mandible): A Randomized Clinical and Genetic Study

Introduction

There are various genes that affect craniofacial development and among the important genes that affect jaw development is distal-less homeobox (DLX) 6 genes. The present study was carried out to determine the role of DLX6 gene variations in mandibular deficiency.

Methods

Thirty subjects having retrognathic mandible were evaluated by clinical examination and assessed using lateral cephalometric radiographs based on cephalometrics for orthognathic surgery (COGS) analysis of hard tissue with N-Pog parameters being less than -13 mm. For the same subjects, saliva samples were taken and sent to biotechnology labs for genetic evaluation. DNA was isolated from salivary samples using a DNA extraction kit and was subjected to polymerase chain reaction (PCR) amplification and sequencing. Single nucleotide polymorphisms (SNP) analysis was done to assess the role of DLX6 gene in these study subjects.

 Results

 All 30 subjects showed N-POG parameters of COGS analysis for hard tissue to be less than -13mm, confirming retrognathic mandible. SNP analysis of subjects showed no SNPs in any EXON of the DLX6 gene for all 30 study samples.

Conclusion

 No variations in DLX6 gene were found in the present study. Further studies are required to investigate other genes that could be involved in the cause of retrognathic mandible with a larger sample size and to include subjects in the sample having features other than mandibular retrognathia like hearing loss, abnormal pinnae, ectrodactyly, cleft palate, developmental delay and abnormal teeth to determine the contribution of DLX6 gene variations in mandibular deficiency. 

Locally Adapted and Organically Grown Landrace and Ancient Spring Cereals-A Unique Source of Minerals in the Human Diet

Consumer interest in local and organic produce, sustainability along the production chain and food products contributing to health, are laying the foundation for local and organic-based diets using nutrient-dense food. Here, we evaluated 25 locally adapted landrace and ancient spring cereal genotypes per location over four locations and three years, for mineral content, nutritional yield and nutrient density. The results showed a large variation in minerals content and composition in the genotypes, but also over cultivation locations, cultivation years and for genotype groups. Highest minerals content was found in oats, while highest content of Zn and Fe was found in ancient wheats. The wheat Diamant brun, the wheat landrace Öland and naked barley showed high mineral values and high content of Zn and Fe when grown in Alnarp. Nutritional yield, of the cereals evaluated here, was high related to values reported internationally but lower than those found in a comparable winter wheat material. The nutrient density was generally high; less than 350 g was needed if any of the evaluated genotype groups were to be used in the daily diet to reach the recommended value of Zn and Fe, while if the suggested Novel Nordic Diet mix was used, only 250 g were needed. A transfer from currently consumed cereals to those in the present study, along the New Nordic Diet path, showed their potential to contribute as sustainable and nutrient-rich sources in the human diet.

Correlations between exhaled nitric oxide, rs28364072 polymorphism of FCER2 gene, asthma control, and inhaled corticosteroid responsiveness in children with asthma

In children with asthma, the responsiveness of inhaled corticosteroids (ICS) is depended on asthma endotype and phenotype. This study aimed to describe the clinical and biological characteristics, and its correlation with polymorphism of rs28364072 in FCER2 of asthmatic children. This work aimed to study the correlation between fractional concentration of exhaled nitric oxide (FE_NO) level and rs28364072 polymorphism of FCER2 gene with ICS responsiveness and disease control in children with asthma. This study was a prospective and descriptive study. All clinical characteristics, FE_NO, blood eosinophil counts (BEC), skin prick test (SPT), total IgE, asthma control test, and FCER2 gene polymorphism were performed for each patient. One hundred and seven asthmatic children who were over 5 years old (9.2 ± 2.6), were included. Patients with FE_NO > 20 ppb had higher percentage of positive SPT, total IgE level, and BEC (89.2 vs 80.0%, 851.1 vs 656.9 UI ml^-1, and 785 ± 576 G L^-1 vs 425 ± 364 G L^-1; respectively). Among them, there were 54.2% of homozygous TT, 36.4% of heterozygous TC, and 9.4% of homozygous CC of rs28364072 polymorphism in FCER2. The percentage of patients with controlled asthma was increasing after 1 month and 3 months (47.1% and 58.8%; respectively). During the study, the ICS was decreasing as indicated by asthma control (348 ± 118 mcg at 1st month vs 329 ± 119 mcg at 3rd month; p < 0.05). CC genotype had the lowest level of increasing FEV1 compared to that in genotype TC and TT (8.4% vs 8.7% and 27.1%; p > 0.05 and p < 0.05; respectively). The percentage of polymorphism in rs28364072 of FCER2 was significant higher in patients with controlled asthma compared to uncontrolled asthma. Asthmatic children with high FE_NO and rs28364072 polymorphism in FCER2 gene are good responders to ICS; however, asthmatic children with homozygous variant CC of rs28364072 are poorly responsive to ICS.

Gene polymorphisms in VEGFA and COL2A1 are associated with response to inhaled corticosteroids in children with asthma

Aim: The purpose of this study was to investigate the involvement of single-nucleotide polymorphisms in VEGFA, TBX21 and COL2A1 in the response to inhaled corticosteroids in asthmatic children. Subjects & methods: Children with mild-to-moderate asthma were enrolled in the study. The SEQUENOM MassARRAY method was used to sequence 27 SNP genotypes. By ranking the data from smallest to largest, we could infer whether the change in distribution of forced expiratory volume in one second/forced vital capcacity (FEV₁/FVC) and fractional exhaled nitric oxide differed between genotype groups. Results: VEGFA rs3025039 T allele carriers had a smaller change in FEV₁ than CC carriers (p = 0.040), and in COL2A1 rs3809324, the frequency of T allele carriers was lower than that of GG carriers (p = 0.048). rs3025039 was also associated with changes in FEV₁/FVC (p = 0.016). Conclusion: VEGFA and COL2A1 polymorphisms are significantly associated with the response to inhaled corticosteroids in asthmatic children.

Asthma and Corticosteroid Responses in Childhood and Adult Asthma

Corticosteroids are the most effective treatment for asthma; inhaled corticosteroids (ICSs) are the first-line treatment for children and adults with persistent symptoms. ICSs are associated with significant improvements in lung function. The anti-inflammatory effects of corticosteroids are mediated by both genomic and nongenomic factors. Variation in the response to corticosteroids has been observed. Patient characteristics, biomarkers, and genetic features may be used to predict response to ICSs. The existence of multiple mechanisms underlying glucocorticoid insensitivity raises the possibility that this might indeed reflect different diseases with a common phenotype.

Sex differences in behavior and neuropharmacology of zebrafish

Sex is an important variable in biomedical research. The zebrafish (Danio rerio) is increasingly utilized as a powerful new model organism in translational neuroscience and pharmacology. Mounting evidence indicates important sex differences in zebrafish behavioral and neuropharmacological responses. Here, we discuss the role of sex in zebrafish central nervous system (CNS) models, their molecular mechanisms, recent findings and the existing challenges in this field. We also emphasize the growing utility of zebrafish models in translational neuropharmacological research of sex differences, fostering future CNS drug discovery and the search for novel sex-specific therapies. Finally, we highlight the interplay between sex and environment in zebrafish models of sex-environment correlations as an important strategy of CNS disease modeling using this aquatic organism.

The role of intraspecies variation in fish neurobehavioral and neuropharmacological phenotypes in aquatic models

Intraspecies variation is common in both clinical and animal research of various brain disorders. Relatively well-studied in mammals, intraspecies variation in aquatic fish models and its role in their behavioral and pharmacological responses remain poorly understood. Like humans and mammals, fishes show high variance of behavioral and drug-evoked responses, modulated both genetically and environmentally. The zebrafish (Danio rerio) has emerged as a particularly useful model organism tool to access neurobehavioral and drug-evoked responses. Here, we discuss recent findings and the role of the intraspecies variance in neurobehavioral, pharmacological and toxicological studies utilizing zebrafish and other fish models. We also critically evaluate common sources of intraspecies variation and outline potential strategies to improve data reproducibility and translatability.

Parkinson's Disease and the Environment

Parkinson's disease (PD) is a heterogeneous neurodegenerative disorder that affects an estimated 10 million sufferers worldwide. The two forms of PD include familial and sporadic, and while the etiology of PD is still largely unknown, the condition is likely to be multifactorial with genetic and environmental factors contributing to disease genesis. Diagnosis of the condition is attained through the observation of cardinal clinical manifestations including resting tremor, muscle rigidity, slowness or loss of movement, and postural instability. Unfortunately, by the time these features become apparent extensive neurological damage has already occurred. A cure for PD has not been identified and the current therapy options are pharmaceutical- and/or surgical-based interventions to treat condition symptoms. There is no specific test for PD and most diagnoses are confirmed by a combination of clinical symptoms and positive responses to dopaminergic drug therapies. The prevalence and incidence of PD vary worldwide influenced by several factors such as age, gender, ethnicity, genetic susceptibilities, and environmental exposures. Here, we will present environmental factors implicated in sporadic PD onset. By understanding the mechanisms in which environmental factors interact with, and affect the brain we can stride toward finding the underlying cause(s) of PD.

Gene-environment interactions in Alzheimer's disease: A potential path to precision medicine

Alzheimer's disease (AD) is the leading cause of dementia in the United States and afflicts >5.7 million Americans in 2018. Therapeutic options remain extremely limited to those that are symptom targeting, while no drugs have been approved for the modification or reversal of the disease itself. Risk factors for AD including aging, the female sex, as well as carrying an APOE4 genotype. These risk factors have been extensively examined in the literature, while less attention has been paid to modifiable risk factors, including lifestyle, and environmental risk factors such as exposures to air pollution and pesticides. This review highlights the most recent data on risk factors in AD and identifies gene by environment interactions that have been investigated. It also provides a suggested framework for a personalized therapeutic approach to AD, by combining genetic, environmental and lifestyle risk factors. Understanding modifiable risk factors and their interaction with non-modifiable factors (age, susceptibility alleles, and sex) is paramount for designing personalized therapeutic interventions.

Molecular characterisation of virulent gene vacA in Helicobacter pylori clinical isolates from patients with gastroduodenal diseases in Assam, India

Background

Helicobacter pylori, the gastric bacterium, is widely known to be one of the most genetically diverse group of organisms whose pathogenesis as well as the diversity in infection outcome may be attributed to a variety of virulent genes.

Aim

This study aimed to study the molecular profile of H. pylori vacA gene by determining the phylogenetic relatedness and genetic diversity of the strains isolated in this region with those of other geographical regions.

Materials and Methods

A total of twenty H. pylori clinical strains were isolated from randomly selected 100 patients suffering from gastroduodenal diseases as well as endoscopically normal patients in a cross-sectional hospital-based setting from January 2016 to May 2017. VacA signal sequence and mid regions of H. pylori were amplified by polymerase chain reaction followed by DNA sequencing and phylogenetic analysis.

Results

VacA s1m1 allelic variant was more prevalent in our study, regardless of the clinical outcomes. Phylogenetic analysis of VacA s1 strains revealed clustering of most of the strains. VacA m1 strains clustered with Bangladesh strains which is a country nearest to India.

Conclusion

Prevalence of VacA s1m1 strains may account for high risk of transmission of this gastric pathogen and the overall risk of acquiring infection. Phylogenetic analysis results suggests the prevalence of high genetic diversity in our region. Our findings may aid in developing a better understanding of the genetic structure of H. pylori and the pathophysiology of associated diseases, thus facilitating the implementation of various treatment options.

Zebrafish models for personalized psychiatry: Insights from individual, strain and sex differences, and modeling gene x environment interactions

Currently becoming widely recognized, personalized psychiatry focuses on unique physiological and genetic profiles of patients to best tailor their therapy. However, the role of individual differences, as well as genetic and environmental factors, in human psychiatric disorders remains poorly understood. Animal experimental models are a valuable tool to improve our understanding of disease pathophysiology and its molecular mechanisms. Due to high reproduction capability, fully sequenced genome, easy gene editing, and high genetic and physiological homology with humans, zebrafish (Danio rerio) are emerging as a novel powerful model in biomedicine. Mounting evidence supports zebrafish as a useful model organism in CNS research. Robustly expressed in these fish, individual, strain, and sex differences shape their CNS responses to genetic, environmental, and pharmacological manipulations. Here, we discuss zebrafish as a promising complementary translational tool to further advance patient-centered personalized psychiatry.

2D association and integrative omics analysis in rice provides systems biology view in trait analysis

The interactions among genes and between genes and environment contribute significantly to the phenotypic variation of complex traits and may be possible explanations for missing heritability. However, to our knowledge no existing tool can address the two kinds of interactions. Here we propose a novel linear mixed model that considers not only the additive effects of biological markers but also the interaction effects of marker pairs. Interaction effect is demonstrated as a 2D association. Based on this linear mixed model, we developed a pipeline, namely PATOWAS. PATOWAS can be used to study transcriptome-wide and metabolome-wide associations in addition to genome-wide associations. Our case analysis with real rice recombinant inbred lines (RILs) at three omics levels demonstrates that 2D association mapping and integrative omics are able to provide a systems biology view into the analyzed traits, leading toward an answer about how genes, transcripts, proteins, and metabolites work together to produce an observable phenotype.

Wenchao Zhang et al. developed a tool for analyzing traits using data generated from genome-wide, transcriptome-wide, and metabolome-wide association studies. They test their approach in rice, providing a systems biology view of identified traits.

Quantitative epigenetics and evolution

Epigenetics refers to chemical modifications of chromatin or transcribed DNA that can influence gene activity and expression without changes in DNA sequence. The last 20 years have yielded breakthroughs in our understanding of epigenetic processes that impact many fields of biology. In this review, we discuss how epigenetics relates to quantitative genetics and evolution. We argue that epigenetics is important for quantitative genetics because: (1) quantitative genetics is increasingly being combined with genomics, and therefore we should expand our thinking to include cellular-level mechanisms that can account for phenotypic variance and heritability besides just those that are hard-coded in the DNA sequence; and (2) epigenetic mechanisms change how phenotypic variance is partitioned, and can thereby change the heritability of traits and how those traits are inherited. To explicate these points, we show that epigenetics can influence all aspects of the phenotypic variance formula: VP (total phenotypic variance) = VG (genetic variance) + VE (environmental variance) + VGxE (genotype-by-environment interaction) + 2COVGE (the genotype-environment covariance) + Vɛ (residual variance), requiring new strategies to account for different potential sources of epigenetic effects on phenotypic variance. We also demonstrate how each of the components of phenotypic variance not only can be influenced by epigenetics, but can also have evolutionary consequences. We argue that no sources of epigenetic effects on phenotypic variance can be easily cast aside in a quantitative genetic research program that seeks to understand evolutionary processes.

Pharmacogenetic and pharmacogenomic considerations of asthma treatment

INTRODUCTION

Pharmacogenetic and pharmacogenomic approaches are already utilized in some areas, such as oncology and cardiovascular disease, for selecting appropriate patients and/or establishing treatment and dosing guidelines. This is not true in asthma although many patients have different responses to drug treatment due to genetic factors. Areas covered: Several genetic factors that affect the pharmacotherapeutic responses to asthma medications, such as β₂-AR agonists, corticosteroids, and leukotriene modifiers and could contribute to significant between-person variability in response are described. Expert opinion: An expanding number of genetic loci have been associated with therapeutic responses to asthma drugs but the individual effect of one single-nucleotide polymorphism is partial. In fact, epigenetic changes can modify genetic effects in time-, environment-, and tissue-specific manners, genes interact together in networks, and nongenetic components such as environmental exposures, gender, nutrients, and lifestyle can significantly interact with genetics to determine the response to therapy. Therefore, well-designed randomized controlled trials or observational studies are now mandatory to define if response to asthma medications in individual patients can be improved by using pharmacogenetic predictors of treatment response. Meanwhile, routine implementation of pharmacogenetics and pharmacogenomics into clinical practice remains a futuristic, far-off challenge for many clinical practices.

Dietary and genetic influences on hemostasis in a Yup'ik Alaska Native population

Fish and marine animals are important components of the subsistence diet of Alaska Native people, resulting in a high ω3 PUFA intake. The historical record for circumpolar populations highlights a tendency for facile bleeding, possibly related to ω3 PUFA effects on platelet activation and/or vitamin K-dependent clotting factors. To evaluate these two scenarios in Yup'ik people of southwestern Alaska, we examined the association between dietary ω3 PUFA intake and activities of clotting factor II, V, fibrinogen, PT, INR, PTT, and sP-selectin in 733 study participants, using the nitrogen isotope ratio of red blood cells as a biomarker of ω3 PUFA consumption. sP-selectin alone correlated strongly and inversely with ω3 PUFA consumption. Approximately 36% of study participants exhibited PIVKA-II values above the threshold of 2 ng/ml, indicative of low vitamin K status. To assess genetic influences on vitamin K status, study participants were genotyped for common vitamin K cycle polymorphisms in VKORC1, GGCX and CYP4F2. Only CYP4F2*3 associated significantly with vitamin K status, for both acute (plasma vitamin K) and long-term (PIVKA-II) measures. These findings suggest: (i) a primary association of ω3 PUFAs on platelet activation, as opposed to vitamin K-dependent clotting factor activity, (ii) that reduced CYP4F2 enzyme activity associates with vitamin K status. We conclude that high ω3 PUFA intake promotes an anti-platelet effect and speculate that the high frequency of the CYP4F2*3 allele in Yup'ik people (~45%) evolved in response to a need to conserve body stores of vitamin K due to environmental limitations on its availability.

Environmental factors and risk of aggressive prostate cancer among a population of New Zealand men - a genotypic approach

Prostate cancer is one of the most significant health concerns for men worldwide. Numerous researchers carrying out molecular diagnostics have indicated that genetic interactions with biological and behavioral factors play an important role in the overall risk and prognosis of this disease. Single nucleotide polymorphisms (SNPs) are increasingly becoming strong biomarker candidates to identify susceptibility to prostate cancer. We carried out a gene × environment interaction analysis linked to aggressive and non-aggressive prostate cancer (PCa) with a number of SNPs. By using this method, we identified the susceptible alleles in a New Zealand population, and examined the interaction with environmental factors. We have identified a number of SNPs that have risk associations both with and without environmental interaction. The results indicate that certain SNPs are associated with disease vulnerability based on behavioral factors. The list of genes with SNPs identified as being associated with the risk of PCa in a New Zealand population is provided in the graphical abstract.

Effects of genetic factors to inhaled corticosteroid response in children with asthma: a literature review

Numerous studies have examined the association between pharmacogenetic effects and the response to inhaled corticosteroids (ICS) in patients with asthma. In fact, several single nucleotide polymorphisms of a number of candidate genes have been identified that might influence the clinical response to ICS in children with asthma. Their direct or indirect effects depend on their role in the inflammatory process in asthma or the anti-inflammatory action of corticosteroids, respectively. Among the genes identified, variants in T-box 21 (TBX21) and Fc fragment of IgE receptor II (FCER2) contribute indirectly to the variability in the response to ICS by altering the inflammatory mechanisms in asthma, while other genes such as corticotropin releasing hormone receptor 1 (CRHR1), nuclear receptor subfamily 3 group C member 1 (NR3C1), stress induced phosphoprotein 1 (STIP1), dual specificity phosphatase 1 (DUSP1), glucocorticoid induced 1 (GLCCI1), histone deacetylase 1 (HDAC), ORMDL sphingolipid biosynthesis regulator 3 (ORMDL3), and vascular endothelial growth factors (VEGF) directly affect this variability through the anti-inflammatory mechanisms of ICS. The results to date indicate various potential genetic factors associated with the response to ICS, which could be utilized to predict the individual therapeutic response of children with asthma to ICS. Clinical trials are underway and their results are greatly anticipated. Further pharmacogenetic studies are needed to fully understand the effects of genetic variation on the response to ICS in children with asthma.

From direct to indirect lithium targets: a comprehensive review of omics data

Metal ions are critical to a wide range of biological processes.

Gene-Environment Interactions in Stress Response Contribute Additively to a Genotype-Environment Interaction

How combinations of gene-environment interactions collectively give rise to genotype-environment interactions is not fully understood. To shed light on this problem, we genetically dissected an environment-specific poor growth phenotype in a cross of two budding yeast strains. This phenotype is detectable when certain segregants are grown on ethanol at 37°C (‘E37’), a condition that differs from the standard culturing environment in both its carbon source (ethanol as opposed to glucose) and temperature (37°C as opposed to 30°C). Using recurrent backcrossing with phenotypic selection, we identified 16 contributing loci. To examine how these loci interact with each other and the environment, we focused on a subset of four loci that together can lead to poor growth in E37. We measured the growth of all 16 haploid combinations of alleles at these loci in all four possible combinations of carbon source (ethanol or glucose) and temperature (30 or 37°C) in a nearly isogenic population. This revealed that the four loci act in an almost entirely additive manner in E37. However, we also found that these loci have weaker effects when only carbon source or temperature is altered, suggesting that their effect magnitudes depend on the severity of environmental perturbation. Consistent with such a possibility, cloning of three causal genes identified factors that have unrelated functions in stress response. Thus, our results indicate that polymorphisms in stress response can show effects that are intensified by environmental stress, thereby resulting in major genotype-environment interactions when multiple of these variants co-occur.

Determining the genetic and molecular mechanisms that give rise to genotype-environment interaction (‘GxE’) is important for many areas of biology, including agriculture, evolution, and medicine. To help advance knowledge regarding this topic, we dissect the genetic basis of an example of GxE in which certain Saccharomyces cerevisiae cross progeny show extremely poor growth specifically on ethanol at 37°C. This environment differs from the standard condition used for culturing budding yeast in both its carbon source (ethanol as opposed to glucose) and temperature (37°C as opposed to 30°C). We provide evidence that poor growth on ethanol at 37°C is caused by a number of predominantly additive loci that individually exhibit gene-environment interactions with both carbon source and temperature. These loci show their largest effects when carbon source and temperature are simultaneously modified, indicating their effect magnitudes may be influenced by the severity of environmental stress. Consistent with this possibility, we clone three causal genes and find they encode functionally unrelated components of stress response. Our work suggests that polymorphisms in stress response can contribute additively to genotype-environment interactions that vary in intensity across conditions in a stress level-dependent manner.

Oesophageal squamous cell carcinoma (ESCC): Advances through omics technologies, towards ESCC salivaomics

Oesophageal Squamous Cell Carcinoma (ESCC) is one of the two main subtypes of oesophageal cancer, affecting mainly populations in Asia. Though there have been great efforts to develop methods for a better prognosis, there is still a limitation in the staging of this affection. As a result, ESCC is detected at advances stages, when the interventions on the patient do not have such a positive outcome, leading in many cases to recurrence and to a very low 5-year survival rate, causing high mortality. A way to decrease the number of deaths is the use of biomarkers that can trace the advance of the disease at early stages, when surgical or chemotherapeutic methodologies would have a greater effect on the evolution of the subject. The new high throughput omics technologies offer an unprecedented chance to screen for thousands of molecules at the same time, from which a new set of biomarkers could be developed. One of the most convenient types of samples is saliva, an accessible body fluid that has the advantage of being non-invasive for the patient, being easy to store or to process. This review will focus on the current status of the new omics technologies regarding salivaomics in ESCC, or when not evaluated yet, the achievements in related diseases.

Multi-locus Genotypes Underlying Temperature Sensitivity in a Mutationally Induced Trait

Determining how genetic variation alters the expression of heritable phenotypes across conditions is important for agriculture, evolution, and medicine. Central to this problem is the concept of genotype-by-environment interaction (or 'GxE'), which occurs when segregating genetic variation causes individuals to show different phenotypic responses to the environment. While many studies have sought to identify individual loci that contribute to GxE, obtaining a deeper understanding of this phenomenon may require defining how sets of loci collectively alter the relationship between genotype, environment, and phenotype. Here, we identify combinations of alleles at seven loci that control how a mutationally induced colony phenotype is expressed across a range of temperatures (21, 30, and 37 °C) in a panel of yeast recombinants. We show that five predominant multi-locus genotypes involving the detected loci result in trait expression with varying degrees of temperature sensitivity. By comparing these genotypes and their patterns of trait expression across temperatures, we demonstrate that the involved alleles contribute to temperature sensitivity in different ways. While alleles of the transcription factor MSS11 specify the potential temperatures at which the trait can occur, alleles at the other loci modify temperature sensitivity within the range established by MSS11 in a genetic background- and/or temperature-dependent manner. Our results not only represent one of the first characterizations of GxE at the resolution of multi-locus genotypes, but also provide an example of the different roles that genetic variants can play in altering trait expression across conditions.

Mapping asthma-associated variants in admixed populations

Admixed populations arise when two or more previously isolated populations interbreed. Mapping asthma susceptibility loci in an admixed population using admixture mapping (AM) involves screening the genome of individuals of mixed ancestry for chromosomal regions that have a higher frequency of alleles from a parental population with higher asthma risk as compared with parental population with lower asthma risk. AM takes advantage of the admixture created in populations of mixed ancestry to identify genomic regions where an association exists between genetic ancestry and asthma (in contrast to between the genotype of the marker and asthma). The theory behind AM is that chromosomal segments of affected individuals contain a significantly higher-than-average proportion of alleles from the high-risk parental population and thus are more likely to harbor disease-associated loci. Criteria to evaluate the applicability of AM as a gene mapping approach include: (1) the prevalence of the disease differences in ancestral populations from which the admixed population was formed; (2) a measurable difference in disease-causing alleles between the parental populations; (3) reduced linkage disequilibrium (LD) between unlinked loci across chromosomes and strong LD between neighboring loci; (4) a set of markers with noticeable allele-frequency differences between parental populations that contributes to the admixed population (single nucleotide polymorphisms (SNPs) are the markers of choice because they are abundant, stable, relatively cheap to genotype, and informative with regard to the LD structure of chromosomal segments); and (5) there is an understanding of the extent of segmental chromosomal admixtures and their interactions with environmental factors. Although genome-wide association studies have contributed greatly to our understanding of the genetic components of asthma, the large and increasing degree of admixture in populations across the world create many challenges for further efforts to map disease-causing genes. This review, summarizes the historical context of admixed populations and AM, and considers current opportunities to use AM to map asthma genes. In addition, we provide an overview of the potential limitations and future directions of AM in biomedical research, including joint admixture and association mapping for asthma and asthma-related disorders.

Asymmetric Evolutionary Games

Evolutionary game theory is a powerful framework for studying evolution in populations of interacting individuals. A common assumption in evolutionary game theory is that interactions are symmetric, which means that the players are distinguished by only their strategies. In nature, however, the microscopic interactions between players are nearly always asymmetric due to environmental effects, differing baseline characteristics, and other possible sources of heterogeneity. To model these phenomena, we introduce into evolutionary game theory two broad classes of asymmetric interactions: ecological and genotypic. Ecological asymmetry results from variation in the environments of the players, while genotypic asymmetry is a consequence of the players having differing baseline genotypes. We develop a theory of these forms of asymmetry for games in structured populations and use the classical social dilemmas, the Prisoner’s Dilemma and the Snowdrift Game, for illustrations. Interestingly, asymmetric games reveal essential differences between models of genetic evolution based on reproduction and models of cultural evolution based on imitation that are not apparent in symmetric games.

Biological interactions, even between members of the same species, are almost always asymmetric due to differences in size, access to resources, or past interactions. However, classical game-theoretical models of evolution fail to account for sources of asymmetry in a comprehensive manner. Here, we extend the theory of evolutionary games to two general classes of asymmetry arising from environmental variation and individual differences, covering much of the heterogeneity observed in nature. If selection is weak, evolutionary processes based on asymmetric interactions behave macroscopically like symmetric games with payoffs that may depend on the resource distribution in the population or its structure. Asymmetry uncovers differences between genetic and cultural evolution that are not apparent when interactions are symmetric.

Nonalcoholic steatohepatitis in precision medicine: Unraveling the factors that contribute to individual variability

There are numerous factors in individual variability that make the development and implementation of precision medicine a challenge in the clinic. One of the main goals of precision medicine is to identify the correct dose for each individual in order to maximize therapeutic effect and minimize the occurrence of adverse drug reactions. Many promising advances have been made in identifying and understanding how factors such as genetic polymorphisms can influence drug pharmacokinetics (PK) and contribute to variable drug response (VDR), but it is clear that there remain many unidentified variables. Underlying liver diseases such as nonalcoholic steatohepatitis (NASH) alter absorption, distribution, metabolism, and excretion (ADME) processes and must be considered in the implementation of precision medicine. There is still a profound need for clinical investigation into how NASH-associated changes in ADME mediators, such as metabolism enzymes and transporters, affect the pharmacokinetics of individual drugs known to rely on these pathways for elimination. This review summarizes the key PK factors in individual variability and VDR and highlights NASH as an essential underlying factor that must be considered as the development of precision medicine advances. A multifactorial approach to precision medicine that considers the combination of two or more risk factors (e.g. genetics and NASH) will be required in our effort to provide a new era of benefit for patients.

Drug disposition alterations in liver disease: extrahepatic effects in cholestasis and nonalcoholic steatohepatitis

INTRODUCTION

The pharmacokinetics (PK) of drugs and xenobiotics, namely pharmaceuticals, is influenced by a host of factors that include genetics, physiological factors and environmental stressors. The importance of disease on the disposition of xenobiotics has been increasingly recognized among medical professionals for alterations in key enzymes and membrane transporters that influence drug disposition and contribute to the development of adverse drug reactions.

AREAS COVERED

This review will survey pertinent literature of how liver disease alters the PKs of drugs and other xenobiotics. The focus will be on nonalcoholic steatohepatitis as well as cholestatic liver diseases. A review of basic pharmacokinetic principles, with a special emphasis on xenobiotic metabolizing enzymes and membrane transporters, will be provided. Specifically, examples of how genetic alterations affect metabolism and excretion, respectively, will be highlighted. Lastly, the idea of 'extrahepatic' regulation will be explored, citing examples of how disease manifestation in the liver may affect drug disposition in distal sites, such as the kidney.

EXPERT OPINION

An expert opinion will be provided highlighting the definite need for data in understanding extrahepatic regulation of membrane transporters in the presence of liver disease and its potential to dramatically alter the PK and toxicokinetic profile of numerous drugs and xenobiotics.

Plasticity regulators modulate specific root traits in discrete nitrogen environments

Plant development is remarkably plastic but how precisely can the plant customize its form to specific environments? When the plant adjusts its development to different environments, related traits can change in a coordinated fashion, such that two traits co-vary across many genotypes. Alternatively, traits can vary independently, such that a change in one trait has little predictive value for the change in a second trait. To characterize such “tunability” in developmental plasticity, we carried out a detailed phenotypic characterization of complex root traits among 96 accessions of the model Arabidopsis thaliana in two nitrogen environments. The results revealed a surprising level of independence in the control of traits to environment – a highly tunable form of plasticity. We mapped genetic architecture of plasticity using genome-wide association studies and further used gene expression analysis to narrow down gene candidates in mapped regions. Mutants in genes implicated by association and expression analysis showed precise defects in the predicted traits in the predicted environment, corroborating the independent control of plasticity traits. The overall results suggest that there is a pool of genetic variability in plants that controls traits in specific environments, with opportunity to tune crop plants to a given environment.

Plants can dramatically alter their development in order to cope with new environmental conditions. Such plasticity is especially evident in the root system since it adopts a particular architecture under one condition, but can change architecture by altering the extent of lateral root branching in a different condition. To explore the extent of root plasticity to the critical nutrient nitrogen we analyzed a natural population of the model plant Arabidopsis in both nitrogen-limiting and nitrogen-rich environments. This revealed that root architecture plasticity appears to be the combined effect of many individual root responses to the environment that are independently modulated. Each aspect, such as lateral root length, number, or density seems to be turned on or off separately, giving the whole system flexibility. We then identified specific genes that control these individual component responses by exploring the genetic variation across the natural population in combination with analyzing which genes respond to nitrogen. Together the results help us gain insights into how the environment shapes plant development. This knowledge can be used to better understand how the growth of our existing crop species might change as the climate varies, and identify new crop varieties that will be robust to such variation.