Polygenic Risk Scores Driving Clinical Change in Glaucoma.

Glaucoma is a clinically heterogeneous disease and the world's leading cause of irreversible blindness. Therapeutic intervention can prevent blindness but relies on early diagnosis, and current clinical risk factors are limited in their ability to predict who will develop sight-threatening glaucoma. The high heritability of glaucoma makes it an ideal substrate for genetic risk prediction, with the bulk of risk being polygenic in nature. Here, we summarize the foundations of glaucoma genetic risk, the development of polygenic risk prediction instruments, and emerging opportunities for genetic risk stratification. Although challenges remain, genetic risk stratification will significantly improve glaucoma screening and management.

shaPRS: Leveraging shared genetic effects across traits or ancestries improves accuracy of polygenic scores.

We present shaPRS, a method that leverages widespread pleiotropy between traits or shared genetic effects across ancestries, to improve the accuracy of polygenic scores. The method uses genome-wide summary statistics from two diseases or ancestries to improve the genetic effect estimate and standard error at SNPs where there is homogeneity of effect between the two datasets. When there is significant evidence of heterogeneity, the genetic effect from the disease or population closest to the target population is maintained. We show via simulation and a series of real-world examples that shaPRS substantially enhances the accuracy of polygenic risk scores (PRSs) for complex diseases and greatly improves PRS performance across ancestries. shaPRS is a PRS pre-processing method that is agnostic to the actual PRS generation method, and as a result, it can be integrated into existing PRS generation pipelines and continue to be applied as more performant PRS methods are developed over time.

Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning.

Methods of estimating polygenic scores (PGSs) from genome-wide association studies are increasingly utilized. However, independent method evaluation is lacking, and method comparisons are often limited. Here, we evaluate polygenic scores derived via seven methods in five biobank studies (totaling about 1.2 million participants) across 16 diseases and quantitative traits, building on a reference-standardized framework. We conducted meta-analyses to quantify the effects of method choice, hyperparameter tuning, method ensembling, and the target biobank on PGS performance. We found that no single method consistently outperformed all others. PGS effect sizes were more variable between biobanks than between methods within biobanks when methods were well tuned. Differences between methods were largest for the two investigated autoimmune diseases, seropositive rheumatoid arthritis and type 1 diabetes. For most methods, cross-validation was more reliable for tuning hyperparameters than automatic tuning (without the use of target data). For a given target phenotype, elastic net models combining PGS across methods (ensemble PGS) tuned in the UK Biobank provided consistent, high, and cross-biobank transferable performance, increasing PGS effect sizes (ß coefficients) by a median of 5.0% relative to LDpred2 and MegaPRS (the two best-performing single methods when tuned with cross-validation). Our interactively browsable online-results and open-source workflow prspipe provide a rich resource and reference for the analysis of polygenic scoring methods across biobanks.

Genotype error due to low-coverage sequencing induces uncertainty in polygenic scoring.

Polygenic scores (PGSs) have emerged as a standard approach to predict phenotypes from genotype data in a wide array of applications from socio-genomics to personalized medicine. Traditional PGSs assume genotype data to be error-free, ignoring possible errors and uncertainties introduced from genotyping, sequencing, and/or imputation. In this work, we investigate the effects of genotyping error due to low coverage sequencing on PGS estimation. We leverage SNP array and low-coverage whole-genome sequencing data (lcWGS, median coverage 0.04×) of 802 individuals from the Dana-Farber PROFILE cohort to show that PGS error correlates with sequencing depth (p = 1.2 × 10-7). We develop a probabilistic approach that incorporates genotype error in PGS estimation to produce well-calibrated PGS credible intervals and show that the probabilistic approach increases classification accuracy by up to 6% as compared to traditional PGSs that ignore genotyping error. Finally, we use simulations to explore the combined effect of genotyping and effect size errors and their implication on PGS-based risk-stratification. Our results illustrate the importance of considering genotyping error as a source of PGS error especially for cohorts with varying genotyping technologies and/or low-coverage sequencing.

mtPGS: Leverage multiple correlated traits for accurate polygenic score construction.

Accurate polygenic scores (PGSs) facilitate the genetic prediction of complex traits and aid in the development of personalized medicine. Here, we develop a statistical method called multi-trait assisted PGS (mtPGS), which can construct accurate PGSs for a target trait of interest by leveraging multiple traits relevant to the target trait. Specifically, mtPGS borrows SNP effect size similarity information between the target trait and its relevant traits to improve the effect size estimation on the target trait, thus achieving accurate PGSs. In the process, mtPGS flexibly models the shared genetic architecture between the target and the relevant traits to achieve robust performance, while explicitly accounting for the environmental covariance among them to accommodate different study designs with various sample overlap patterns. In addition, mtPGS uses only summary statistics as input and relies on a deterministic algorithm with several algebraic techniques for scalable computation. We evaluate the performance of mtPGS through comprehensive simulations and applications to 25 traits in the UK Biobank, where in the real data mtPGS achieves an average of 0.90%-52.91% accuracy gain compared to the state-of-the-art PGS methods. Overall, mtPGS represents an accurate, fast, and robust solution for PGS construction in biobank-scale datasets.

The contributions of rare inherited and polygenic risk to ASD in multiplex families.

Autism spectrum disorder (ASD) has a complex genetic architecture involving contributions from both de novo and inherited variation. Few studies have been designed to address the role of rare inherited variation or its interaction with common polygenic risk in ASD. Here, we performed whole-genome sequencing of the largest cohort of multiplex families to date, consisting of 4,551 individuals in 1,004 families having two or more autistic children. Using this study design, we identify seven previously unrecognized ASD risk genes supported by a majority of rare inherited variants, finding support for a total of 74 genes in our cohort and a total of 152 genes after combined analysis with other studies. Autistic children from multiplex families demonstrate an increased burden of rare inherited protein-truncating variants in known ASD risk genes. We also find that ASD polygenic score (PGS) is overtransmitted from nonautistic parents to autistic children who also harbor rare inherited variants, consistent with combinatorial effects in the offspring, which may explain the reduced penetrance of these rare variants in parents. We also observe that in addition to social dysfunction, language delay is associated with ASD PGS overtransmission. These results are consistent with an additive complex genetic risk architecture of ASD involving rare and common variation and further suggest that language delay is a core biological feature of ASD.

ExPRSweb: An online repository with polygenic risk scores for common health-related exposures.

Complex traits are influenced by genetic risk factors, lifestyle, and environmental variables, so-called exposures. Some exposures, e.g., smoking or lipid levels, have common genetic modifiers identified in genome-wide association studies. Because measurements are often unfeasible, exposure polygenic risk scores (ExPRSs) offer an alternative to study the influence of exposures on various phenotypes. Here, we collected publicly available summary statistics for 28 exposures and applied four common PRS methods to generate ExPRSs in two large biobanks: the Michigan Genomics Initiative and the UK Biobank. We established ExPRSs for 27 exposures and demonstrated their applicability in phenome-wide association studies and as predictors for common chronic conditions. Especially the addition of multiple ExPRSs showed, for several chronic conditions, an improvement compared to prediction models that only included traditional, disease-focused PRSs. To facilitate follow-up studies, we share all ExPRS constructs and generated results via an online repository called ExPRSweb.

Nonadjacent Wireless Electrotherapy for Tissue Repair by a 3D-Printed Bioresorbable Fully Soft Triboelectric Nanogenerator.

Electrotherapy is a promising tissue repair technique. However, electrotherapy devices are frequently complex and must be placed adjacent to injured tissue, thereby limiting their clinical application. Here, we propose a general strategy to facilitate tissue repair by modulating endogenous electric fields with nonadjacent (approximately 44 mm) wireless electrotherapy through a 3D-printed entirely soft and bioresorbable triboelectric nanogenerator based stimulator, without any electrical accessories, which has biomimetic mechanical properties similar to those of soft tissue. In addition, the feasibility of using the stimulator to construct an electrical double layer with tissue for nonadjacent wireless electrotherapy was demonstrated by skin and muscle injury models. The treated groups showed significantly improved tissue repair compared with the control group. In conclusion, we developed a promising electrotherapy strategy and may inspire next-generation electrotherapy for tissue repair.

Canalization of the Polygenic Risk for Common Diseases and Traits in the UK Biobank Cohort.

Since organisms develop and thrive in the face of constant perturbations due to environmental and genetic variation, species may evolve resilient genetic architectures. We sought evidence for this process, known as canalization, through a comparison of the prevalence of phenotypes as a function of the polygenic score (PGS) across environments in the UK Biobank cohort study. Contrasting seven diseases and three categorical phenotypes with respect to 151 exposures in 408,925 people, the deviation between the prevalence-risk curves was observed to increase monotonically with the PGS percentile in one-fifth of the comparisons, suggesting extensive PGS-by-Environment (PGS×E) interaction. After adjustment for the dependency of allelic effect sizes on increased prevalence in the perturbing environment, cases where polygenic influences are greater or lesser than expected are seen to be particularly pervasive for educational attainment, obesity, and metabolic condition type-2 diabetes. Inflammatory bowel disease analysis shows fewer interactions but confirms that smoking and some aspects of diet influence risk. Notably, body mass index has more evidence for decanalization (increased genetic influence at the extremes of polygenic risk), whereas the waist-to-hip ratio shows canalization, reflecting different evolutionary pressures on the architectures of these weight-related traits. An additional 10 % of comparisons showed evidence for an additive shift of prevalence independent of PGS between exposures. These results provide the first widespread evidence for canalization protecting against disease in humans and have implications for personalized medicine as well as understanding the evolution of complex traits. The findings can be explored through an R shiny app at https://canalization-gibsonlab.shinyapps.io/rshiny/.

Cost-effectiveness of preimplantation genetic testing for aneuploidy for women with subfertility in China: an economic evaluation using evidence from the CESE-PGS trial.

BACKGROUND: There are a large number of infertile couples in China, but its treatment is notoriously expensive and not currently covered by insurance. The utility of preimplantation genetic testing for aneuploidy as an adjunct to in vitro fertilization has been debated. OBJECTIVE: To investigate the cost-effectiveness of preimplantation genetic testing for aneuploidy (PGT-A) versus conventional technology in in vitro fertilization (IVF) from the perspective of the healthcare system in China. METHODS: Following the exact steps in the IVF protocol, a decision tree model was developed, based on the data from the CESE-PGS trial and using cost scenarios for IVF in China. The scenarios were compared for costs per patient and cost-effectiveness. One-way sensitivity analysis and probabilistic sensitivity analysis were performed to confirm the robustness of the findings. MAIN OUTCOME MEASURES: Costs per live birth, Costs per patient, Incremental cost-effectiveness for miscarriage prevention. RESULTS: The average costs per live birth of PGT-A were estimated as ¥39230.71, which is about 16.8% higher than that of the conventional treatment. Threshold analysis revealed that PGT-A would need to increase the pregnancy rate of 26.24-98.24% or a cost reduction of ¥4649.29 to ¥1350.71 to achieve the same cost-effectiveness. The incremental costs per prevented miscarriage was approximately ¥45600.23. The incremental cost-effectiveness for miscarriage prevention showed that the willingness to pay would be ¥43422.60 for PGT-A to be cost-effective. CONCLUSION: The present cost-effectiveness analysis demonstrates that embryo selection with PGT­A is not suitable for routine applications from the perspective of healthcare providers in China, given the cumulative live birth rate and the high costs of PGT­A.

Predictive value of 3D ultrasound assessment of endometrial receptivity for PGD/PGS for transfer pregnancy outcome.

OBJECTIVE: To investigate the predictive value of three-dimensional ultrasound assessment of endometrial receptivity in PGD/PGS transplantation patients on pregnancy outcome. METHODS: 280 patients undergoing PGD/PGS transplantation were enrolled and divided into group A and group B according to the patients' pregnancy outcomes. The general conditions, endometrial receptivity indexes of the two groups were compared. Multifactorial logistic regression analysis was used to determine the factors influencing pregnancy outcome in PGD/PGS transplant patients. ROC curves were plotted to analyze the predictive value of 3D ultrasound parameters on pregnancy outcome. The results of the study were validated with patients who underwent FET transplantation, and the patients in the validation group were treated with the same 3D ultrasound examination method and treatment plan as the observation group. RESULTS: The differences in basic situations between two groups were not statistically significant (P > 0.05). The percentage of endometrial thickness, endometrial blood flow, and endometrial blood flow classification type II + II were higher in group A than in group B (P < 0.05). Multifactorial logistic regression analysis showed that endometrial thickness, endometrial blood flow and endometrial blood flow classification were influencing factors of pregnancy outcome in PGD/PGS patients. The sensitivity of predicting pregnancy outcome based on the results of transcatheter 3D ultrasound was 91.18%, the specificity was 82.35%, and the accuracy was 90.00%, which has a high predictive value. CONCLUSION: 3D ultrasound can predict pregnancy outcome by assessing the endometrial receptivity of PGD/PGS transplantation, in which endometrial thickness and endometrial blood flow have a good predictive value.

Human Genetics Society of Australasia Position Statement: Use of Polygenic Scores in Clinical Practice and Population Health.

Considerable progress continues to be made with regards to the value and use of disease associated polygenic scores (PGS). PGS aim to capture a person's genetic liability to a condition, disease, or a trait, combining information across many risk variants and incorporating their effect sizes. They are already available for clinicians and consumers to order in Australasia. However, debate is ongoing over the readiness of this information for integration into clinical practice and population health. This position statement provides the viewpoint of the Human Genetics Society of Australasia (HGSA) regarding the clinical application of disease-associated PGS in both individual patients and population health. The statement details how PGS are calculated, highlights their breadth of possible application, and examines their current challenges and limitations. We consider fundamental lessons from Mendelian genetics and their continuing relevance to PGS, while also acknowledging the distinct elements of PGS. Use of PGS in practice should be evidence based, and the evidence for the associated benefit, while rapidly emerging, remains limited. Given that clinicians and consumers can already order PGS, their current limitations and key issues warrant consideration. PGS can be developed for most complex conditions and traits and can be used across multiple clinical settings and for population health. The HGSA's view is that further evaluation, including regulatory, implementation and health system evaluation are required before PGS can be routinely implemented in the Australasian healthcare system.

BmPxt1 mediated immune response by regulating PGE2 in silkworm, Bombyx mori.

Prostaglandins (PGs) mediates the immune response of insects to multiple stimuli. Mammalian cyclooxygenase (COXs) is a key enzyme in the synthesis of PGs, and peroxinectin (Pxt) may have similar functions in some sequenced insect genomes. As a representative of Lepidoptera, the silkworm also contains PGs, but its synthetic pathway is not clear. We cloned a full-length cDNA encoding a Pxt, designated as BmPxt1, from silkworm. Sequence alignment analysis showed that the protein encoded by BmPxt1 has a conserved domain similar to Pxts, and its catalytic site is shared with the Pxt of Manduca sexta, which also produces PGs. The expression of BmPxt1 gene was the highest in the hemocytes and was induced by Nuclear Polyhedrosis Virus (NPV) challenge in the detected tissues. Moreover, we found that dsPxt1 treatment deficiency down-regulated BmPxt1 transcript levels and efficiently inhibiting hemocyte-spreading and nodule formation in silkworm. Hemocyte-spreading, nodule formation, phenoloxidase (PO) and AMP genes (attacin, defencin and moricin) were also inhibited by aspirin, a COX inhibitor. Treatment by PGE2 but not arachidonic acid (AA) rescued the immunosuppression; PGs concentrations was also inhibited by aspirin. PGE2, but not AA, treatment rescued the PGs concentrations. The COX inhibitor, aspirin, impaired the innate immune response including nodulation, encapsulation, and melanization in silkworm, while PGE2, but not arachidonic acid (AA), partially reversed these effects of aspirin. Recombinant BmsPxt1 significantly induced PO activation in larvae hemolymph, PGs concentrations and encapsulation of agarose beads. Injection of recombinant BmsPxt1 into larvae resulted in increased transcript levels of AMP genes. Our results confirmed that BmPxt1 was involved in the synthesis of PGs in the innate immune response of silkworm larvae, and provided new information for the role of BmsPxt1 secreted by silkworm in activating PO and antimicrobial peptides.

Environment-by-PGS Interaction in the Classical Twin Design: An Application to Childhood Anxiety and Negative Affect.

One type of genotype-environment interaction occurs when genetic effects on a phenotype are moderated by an environment; or when environmental effects on a phenotype are moderated by genes. Here we outline these types of genotype-environment interaction models, and propose a test of genotype-environment interaction based on the classical twin design, which includes observed genetic variables (polygenic scores: PGSs) that account for part of the genetic variance of the phenotype. We introduce environment-by-PGS interaction and the results of a simulation study to address statistical power and parameter recovery. Next, we apply the model to empirical data on anxiety and negative affect in children. The power to detect environment-by-PGS interaction depends on the heritability of the phenotype, and the strength of the PGS. The simulation results indicate that under realistic conditions of sample size, heritability and strength of the interaction, the environment-by-PGS model is a viable approach to detect genotype-environment interaction. In 7-year-old children, we defined two PGS based on the largest genetic association studies for 2 traits that are genetically correlated to childhood anxiety and negative affect, namely major depression (MDD) and intelligence (IQ). We find that common environmental influences on negative affect are amplified for children with a lower IQ-PGS.

Cognitive trajectories diverge by genetic risk in a preclinical longitudinal cohort.

INTRODUCTION: We sought to characterize the timing of changes in cognitive trajectories related to genetic risk using the apolipoprotein E (APOE) score, a continuous measure of Alzheimer's disease (AD) risk. We also aimed to determine whether that timing was different when genetic risk was measured using an AD polygenic risk score (PRS) that contains APOE. METHODS: We analyzed trajectories (N ≈1135) for four neuropsychological composite scores using mixed effects regression for longitudinal change across APOE scores and PRS of participants in the Wisconsin Registry for Alzheimer's Prevention, a longitudinal study of adults aged 40 to 70 at baseline, with a median participant follow-up time of 7.8 years. RESULTS: We found a significant non-linear age-by-APOE score interaction in predicting cognitive decline. Cognitive trajectories diverged by APOE score at approximately 65 years of age. A 0.5 standard deviation difference in cognition between extreme percentiles of the PRS was predicted to occur 1 to 2 years before that of the APOE score. DISCUSSION: Cognitive decline differs across time and APOE score. Estimates did not substantially shift with the AD PRS. HIGHLIGHTS: The apolipoprotein E (APOE) score, a continuous measure, accounts for non-linear genetic risk of Alzheimer's disease. Non-linear age interacts with the APOE score to affect cognition. Cognitive decline starts to differ by APOE score levels at approximately age 65. Cognitive decline timing by polygenic risk (including APOE) is similar to APOE alone.

IVF outcomes of embryos with abnormal PGT-A biopsy previously refused transfer: a prospective cohort study.

STUDY QUESTION: What are the outcomes for patients who choose to move embryos diagnosed as abnormal by preimplantation genetic testing for aneuploidy (PGT-A) to a new institution for transfer after the diagnosing institution refused to transfer them? SUMMARY ANSWER: Many patients seek to have selected embryos with PGT-A abnormal trophectoderm biopsies transferred recognizing that these embryos can still offer a chance of pregnancy and live birth. WHAT IS KNOWN ALREADY: : PGT-A is a widely practiced method of selecting embryos for transfer based on biopsy of a few cells. Many clinical practices refuse to transfer PGT-A abnormal embryos even when there are no other 'normal' embryos available. STUDY DESIGN, SIZE, DURATION: This is a prospective cohort of 69 couples who, since 2014, moved a total of 444 PGT-A abnormal embryos previously refused transfer at their parent institutions to our practice. Among these, 50 patients have, thus far, undergone 57 transfer cycles of 141 embryos. PARTICIPANTS/MATERIALS, SETTING, METHODS: Embryos diagnosed at other institutions by PGT-A as abnormal (mostly using next generation sequencing) were moved to our academically affiliated private fertility and research center in New York City. Female age at retrieval was 41.35 ± 3.98 years, 74% were Caucasian, 12% Asian and 10% were of African descent. All embryos identified as PGT-A abnormal among prospectively identified couples were recorded in our center's registry. MAIN RESULTS AND THE ROLE OF CHANCE: Among the 144 embryos transferred 102 (72.3%) had only 1 or 2 chromosomal abnormalities, 30 (21.3%) had 3 or more and 9 (6.4%) were 'undiagnosed' because of degraded DNA, yet still had been refused transfer. Transfer of PGT-A abnormal embryos resulted in 8 live births, 11 miscarriages and no voluntary terminations. One child was born with a segmental duplication and required repair of coarctation of the aorta as a newborn. Many couples with only PGT-A abnormal embryos are willing to have their PGT-A abnormal embryos transferred and such transfers can result in the establishment of ongoing euploid pregnancies and live births. LIMITATIONS, REASONS FOR CAUTION: Findings in this case series represent couples who chose to have their embryos transferred after having been refused transfer elsewhere and may not be representative of the wider population of couples undergoing IVF with PGT-A in general. Not all abnormal phenotypes present in the immediate postnatal period so it will be important to continue to follow the development of these children. WIDER IMPLICATIONS OF THE FINDINGS: PGT-A can result in a clinics refusal to transfer embryos with abnormal PGT-A biopsies, even those with mosaic findings, consequently large numbers of infertile women are prematurely advised that their only chance of motherhood is through third-party egg-donation. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by intramural funds from the Center for Human Reproduction and the not-for-profit research Foundation for Reproductive Medicine, both in New York, NY, USA. N.G. and D.H.B. are listed as co-inventors on several U.S. patents. One of these patents (US Patent# 7,615,544) relates to pre-supplementation of hypo-androgenic infertile women with androgens, such as DHEA and testosterone and, therefore, at least peripherally related to the subject of this manuscript. N.G. and D.F.A. also received travel funds and speaker honoraria from several pharmaceutical and medical device companies, though none related to the here presented subject and manuscript. N.G. is a shareholder in Fertility Nutraceuticals and he and D.H.B. receive royalty payments from Fertility Nutraceuticals LLC. TRIAL REGISTRATION NUMBER: N/A.

Father absence, age at menarche, and genetic confounding: A replication and extension using a polygenic score.

Father absence has a small but robust association with earlier age at menarche (AAM), likely reflecting both genetic confounding and an environmental influence on life history strategy development. Studies that have attempted to disambiguate genetic versus environmental contributions to this association have shown conflicting findings, though genomic-based studies have begun to establish the role of gene-environment interplay in the father absence/AAM literature. The purpose of this study was to replicate and extend prior genomic work using the Avon Longitudinal Study of Parents and Children (ALSPAC), a prospective longitudinal cohort study (N = 2,685), by (a) testing if an AAM polygenic score (PGS) could account for the father absence/AAM association, (b) replicating G×E research on lin-28 homolog B (LIN28B) variation and father absence, and (c) testing the G×E hypothesis using the PGS. Results showed that the PGS could not explain the father absence/AAM association and there was no interaction between father absence and the PGS. Findings using LIN28B largely replicated prior work that showed LIN28B variants predicted later AAM in father-present girls, but this AAM-delaying effect was absent or reversed in father-absent girls. Findings are discussed in terms genetic confounding, the unique biological role of LIN28B, and using PGSs for G×E tests.

The influence of harshness and unpredictability on female sexual development: Addressing gene-environment interplay using a polygenic score.

Recent developments in the application life history theory to human development indicate two fundamental dimension of the early environment - harshness and unpredictability - are key regulators life history strategies. Few studies have examined the manner with which these dimensions influence development, though age at menarche (AAM) and age at first sexual intercourse have been proposed as possible mechanisms among women. Data from the Avon Longitudinal Study of Parents and Children (N = 3,645) were used to examine direct and indirect effects of harshness (financial difficulties) and unpredictability (paternal transitions) on lifetime and past year sexual partners during adolescence and young adulthood. Genetic confounding was addressed using an AAM polygenic score (PGS) and potential gene-by-environment interactions were also evaluated using the PGS. Path model results showed only harshness was directly related to AAM. Harshness, unpredictability, and AAM were indirectly related to lifetime and past year sexual partner number via age at first sexual intercourse. The PGS did not account for any of the associations and no significant interactions were detected. Implications of these results for developmental models derived from life history theory are discussed as well as the role of PGSs in gene-environment interplay research.

Structural and genetic insights into a poly-γ-glutamic acid with in vitro antioxidant activity of Bacillus velezensis VCN56.

Poly-γ­glutamic acid (γ­PGA) produced by Bacillus species is a natural biopolymer, which is widely used in various fields including food, pharmaceuticals, and cosmetics. In this study, the screening of 19 Bacillus isolates derived from traditionally fermented foods revealed that Bacillus velezensis VCN56 was the most potent γ­PGA producer. The maximum concentration of crude γ­PGA was 32.9 ± 1.5 g/L in the PGA-3 medium containing glycerol, citric acid, sodium glutamate, NH4Cl, and starch. The resulting γ-PGA was purified and then characterized by HPLC, FTIR, and 1H-NMR analyses. Molecular weight of purified γ­PGA was estimated to be 98 kDa with a polydisperse index of 2.04. Notably, the pure γ­PGA showed significant in vitro antioxidant scavenging activities against 1,1-diphenyl-2-picrylhydrazyl (72.0 ± 1.5%), hydroxyl (81.0 ± 0.6%), and superoxide (43.9 ± 0.8%) radicals at the concentration of 4 mg/mL. Using whole-genome sequencing, the genetic organization of pgs operon responsible for γ­PGA biosynthesis in B. velezensis VCN56 differs from those in other Bacillus genomes. Further genome analysis revealed metabolic pathways for γ-PGA production and degradation. For the first time, the present study provides a better understanding of γ-PGA with a promising antioxidant activity produced by B. velezensis at the phenotypic, biochemical, and genomic levels, which hold potential applications in the foods, cosmetics, and pharmaceutical industries.

Where the genome meets the connectome: Understanding how genes shape human brain connectivity.

The integration of modern neuroimaging methods with genetically informative designs and data can shed light on the molecular mechanisms underlying the structural and functional organization of the human connectome. Here, we review studies that have investigated the genetic basis of human brain network structure and function through three complementary frameworks: (1) the quantification of phenotypic heritability through classical twin designs; (2) the identification of specific DNA variants linked to phenotypic variation through association and related studies; and (3) the analysis of correlations between spatial variations in imaging phenotypes and gene expression profiles through the integration of neuroimaging and transcriptional atlas data. We consider the basic foundations, strengths, limitations, and discoveries associated with each approach. We present converging evidence to indicate that anatomical connectivity is under stronger genetic influence than functional connectivity and that genetic influences are not uniformly distributed throughout the brain, with phenotypic variation in certain regions and connections being under stronger genetic control than others. We also consider how the combination of imaging and genetics can be used to understand the ways in which genes may drive brain dysfunction in different clinical disorders.