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Asthma is a chronic inflammatory disorder with a strong genetic inheritance. Although more than 100 loci were reported through the genome-wide association study of European populations, the genetic underpinning of asthma in African American individuals remains largely elusive.We aimed to identify genetic loci associated with asthma in African American individuals.Three cohorts were genotyped at the Children's Hospital of Philadelphia by using the Illumina single-nucleotide polymorphism array platform. Genotype imputation was performed by using the Trans-Omics for Precision Medicine (TOPMed) reference panel, which includes whole genome sequencing data from more than 100,000 individuals. A meta-analysis of 3 Children's Hospital of Philadelphia cohorts and 10 Consortium on Asthma among African Ancestry Populations in the Americas cohorts, totaling 19,628 subjects, was conducted to identify genetic loci associated with asthma in African American individuals.Our study identified 12 loci surpassing the classical genome-wide significance threshold (5 × 10Our findings provide candidate genetic loci for therapeutic target identification and prioritization for African populations.

Objectives JDM is a serious autoimmune and complex genetic disease. Another autoimmune genetic disease, type 1 diabetes (T1D), has been observed for significantly increased prevalence in families with JDM, while increased JDM risk has also been observed in T1D cases. This study aimed to study whether these two autoimmune diseases, JDM and T1D, share common genetic susceptibility. Methods From 169 JDM families, 121 unrelated cases with European ancestry (EA) were identified by genome-wide genotyping, principal component analysis and identical-by-descent (IBD) analysis. T1D genetic risk score (GRS) were calculated in these cases and were compared with 361 EA T1D cases and 1943 non-diabetes EA controls. A total of 113 cases of the 121 unrelated European cases were sequenced by whole exome sequencing. Results We observed increased T1D GRS in JDM cases (P = 9.42E-05). Using whole exome sequencing, we uncovered the T1D genes, phospholipase B1, cystic fibrosis transmembrane conductance regulator, tyrosine hydroxylase, CD6 molecule, perforin 1 and dynein axonemal heavy chain 2, potentially associated with JDM by the burden test of rare functional coding variants. Conclusion Novel mechanisms of JDM related to these T1D genes are suggested by this study, which may imply novel therapeutic targets for JDM and warrant further study.

Precise risk prediction of type 1 diabetes (T1D) facilitates early intervention and identification of risk factors prior to irreversible beta-islet cell destruction, and can significantly improve T1D prevention and clinical care. Sharp et al. (2019) developed a genetic risk scoring (GRS) system for T1D (T1D-GRS2) capable of predicting T1D risk in children of European ancestry. The T1D-GRS2 was developed on the basis of causal genetic variants, thus may be applicable to minor populations, while a trans-ethnic GRS for T1D may avoid the exacerbation of health disparities due to the lack of genomic information in minorities. Here, we describe a T1D-GRS2 calculator validated in two independent cohorts, including African American (AA) children and European American (EA) children. Participants were recruited by the Center for Applied Genomics (CAG) at the Children’s Hospital of Philadelphia (CHOP). It demonstrates that GRS2 is applicable to the T1D risk prediction in the AA cohort, while population-specific thresholds are needed for different populations. The study highlights the potential to further improve T1D-GRS2 performance with the inclusion of additional genetic markers.

BackgroundWhile polygenic risk scores hold significant promise in estimating an individual’s risk of developing a complex trait such as obesity, their application in the clinic has, to date, been limited by a lack of data from non-European populations. As a collaboration model of the International Hundred K+ Cohorts Consortium (IHCC), we endeavored to develop a globally applicable trans-ethnic PRS for body mass index (BMI) through this relatively new international effort.MethodsThe PRS model was developed trained and tested at the Center for Applied Genomics (CAG) of The Children’s Hospital of Philadelphia (CHOP) based on a BMI meta-analysis from the GIANT consortium. The validated PRS models were subsequently disseminated to the participating sites. Scores were generated by each site locally on their cohorts and summary statistics returned to CAG for final analysis.ResultsWe show that in the absence of a well powered trans-ethnic GWAS from which to derive SNPs and effect estimates, trans-ethnic scores can be generated from European ancestry GWAS using Bayesian approaches such as LDpred to adjust the summary statistics using trans-ethnic linkage disequilibrium reference panels. The ported trans-ethnic scores outperform population specific-PRS across all non-European ancestry populations investigated including East Asians and three-way admixed Brazilian cohort.ConclusionsWidespread use of PRS in the clinic is hampered by a lack of genotyping data in individuals of non-European ancestry for the vast majority of traits. Here we show that for a truly polygenic trait such as BMI adjusting the summary statistics of a well powered European ancestry study using trans-ethnic LD reference results in a score that is predictive across a range of ancestries including East Asians and three-way admixed Brazilians.

BackgroundAlzheimer’s disease (AD) is a complex multifactorial progressive dementia affecting all human populations. As a collaboration model between the International Hundred K+ Cohorts Consortium (IHCC) and the Davos Alzheimer Collaborative (DAC), our aim was to develop a trans-ethnic genomic informed risk assessment (GIRA) algorithm for AD.MethodsThe GIRA model was created to include a polygenic risk score (PRS) calculated from the AD GWAS loci, theAPOEhaplotypes, and non-genetic covariates including age, sex and first 3 principal components of population substructure. The model was first validated using a ancestrally diverse dataset from the eMERGE network, and subsequently validated in a South-Asian population in the UK and 3 East-Asian populations. The distributions of the PRS scores were also explored in populations from 3 African regions. In two validation sites, the PRS was tested for associated with the levels of plasma proteomics markers.ResultsWe created a trans-ethnic GIRA model for the risk prediction of AD and validated the performance of the GIRA model in different populations. The proteomic study in the participant sites identified proteins related to female infertility and autoimmune thyroiditis and associated with the risk scores of AD, highlighting molecular mechanisms underlying the previously observed correlations between these clinical phenotypes.ConclusionsAs the initial effort by the IHCC to leverage existing large scale datasets in a collaborative setting with DAC, we developed a trans-ethnic GIRA for AD with the potential of identifying individuals at high risk of developing AD for future clinical applications. The PRS scores in this model also contribute new research discoveries for the molecular pathogenesis of AD as demonstrated by the proteomic data.

Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune .

Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk.To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores (PRS), monogenic risks, family history, and clinical risk assessments via a Genome Informed Risk Assessment (GIRA) report and will assess uptake of care recommendations after return of results.GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022.Return of a novel report for communicating monogenic, polygenic, and family history based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

High BMI is associated with many comorbidities and mortality. This study aimed to elucidate the overall clinical risk of obesity using a genome- and phenome-wide approach.This study performed a phenome-wide association study of BMI using a clinical cohort of 736,726 adults. This was followed by genetic association studies using two separate cohorts: one consisting of 65,174 adults in the Electronic Medical Records and Genomics (eMERGE) Network and another with 405,432 participants in the UK Biobank.Class 3 obesity was associated with 433 phenotypes, representing 59.3% of all billing codes in individuals with severe obesity. A genome-wide polygenic risk score for BMI, accounting for 7.5% of variance in BMI, was associated with 296 clinical diseases, including strong associations with type 2 diabetes, sleep apnea, hypertension, and chronic liver disease. In all three cohorts, 199 phenotypes were associated with class 3 obesity and polygenic risk for obesity, including novel associations such as increased risk of renal failure, venous insufficiency, and gastroesophageal reflux.This combined genomic and phenomic systematic approach demonstrated that obesity has a strong genetic predisposition and is associated with a considerable burden of disease across all disease classes.

Background Previous study has shown that dyslipidemia is common in patients with Sickle cell disease (SCD) and is associated with more serious SCD complications. Methods This study investigated systematically dyslipidemia in SCD using a state-of-art nuclear magnetic resonance (NMR) metabolomics platform, including 147 pediatric cases with SCD and 1234 controls without SCD. We examined 249 metabolomic biomarkers, including 98 biomarkers for lipoprotein subclasses, 70 biomarkers for relative lipoprotein lipid concentrations, plus biomarkers for fatty acids and phospholipids. Results Specific patterns of hypolipoproteinemia and hypocholesterolemia in pediatric SCD were observed in lipoprotein subclasses other than larger VLDL subclasses. Triglycerides are not significantly changed in SCD, except increased relative concentrations in lipoprotein subclasses. Decreased plasma FFAs (including total-FA, SFA, PUFA, Omega-6, and linoleic acid) and decreased plasma phospholipids were observed in SCD. Conclusion This study scrutinized, for the first time, lipoprotein subclasses in pediatric patients with SCD, and identified SCD-specific dyslipidemia from altered lipoprotein metabolism. The findings of this study depict a broad panorama of lipid metabolism and nutrition in SCD, suggesting the potential of specific dietary supplementation of the deficient nutrients for the management of SCD.

Supplemental Digital Content is available in the text., Background: Abdominal aortic aneurysm (AAA) is an important cause of cardiovascular mortality; however, its genetic determinants remain incompletely defined. In total, 10 previously identified risk loci explain a small fraction of AAA heritability. Methods: We performed a genome-wide association study in the Million Veteran Program testing ≈18 million DNA sequence variants with AAA (7642 cases and 172 172 controls) in veterans of European ancestry with independent replication in up to 4972 cases and 99 858 controls. We then used mendelian randomization to examine the causal effects of blood pressure on AAA. We examined the association of AAA risk variants with aneurysms in the lower extremity, cerebral, and iliac arterial beds, and derived a genome-wide polygenic risk score (PRS) to identify a subset of the population at greater risk for disease. Results: Through a genome-wide association study, we identified 14 novel loci, bringing the total number of known significant AAA loci to 24. In our mendelian randomization analysis, we demonstrate that a genetic increase of 10 mm Hg in diastolic blood pressure (odds ratio, 1.43 [95% CI, 1.24–1.66]; P=1.6×10−6), as opposed to systolic blood pressure (odds ratio, 1.06 [95% CI, 0.97–1.15]; P=0.2), likely has a causal relationship with AAA development. We observed that 19 of 24 AAA risk variants associate with aneurysms in at least 1 other vascular territory. A 29-variant PRS was strongly associated with AAA (odds ratioPRS, 1.26 [95% CI, 1.18–1.36]; PPRS=2.7×10−11 per SD increase in PRS), independent of family history and smoking risk factors (odds ratioPRS+family history+smoking, 1.24 [95% CI, 1.14–1.35]; PPRS=1.27×10−6). Using this PRS, we identified a subset of the population with AAA prevalence greater than that observed in screening trials informing current guidelines. Conclusions: We identify novel AAA genetic associations with therapeutic implications and identify a subset of the population at significantly increased genetic risk of AAA independent of family history. Our data suggest that extending current screening guidelines to include testing to identify those with high polygenic AAA risk, once the cost of genotyping becomes comparable with that of screening ultrasound, would significantly increase the yield of current screening at reasonable cost.

The transition state of the Vmax mutant of AMP nucleosidase from Azotobacter vinelandii [Leung, H. B.,Schramm, V. L. (1981) J. Biol. Chem. 256, 12823-12829] has been characterized by heavy-atom kinetic isotope effects in the presence and absence of MgATP, the allosteric activator. The enzyme catalyzes hydrolysis of the N-glycosidic bond of AMP at approximately 2% of the rate of the normal enzyme with only minor changes in the Km for substrate, the activation constant for MgATP, and the Ki for formycin 5'-phosphate, a tight-binding competitive inhibitor. Isotope effects were measured as a function of the allosteric activator concentration that increases the turnover number of the enzyme from 0.006 s-1 to 1.2 s-1. The kinetic isotope effects were measured with the substrates [1'-3H]AMP, [2'-2H]AMP, [2'-2H]AMP, [9-15N]AMP, and [1',9-14C, 15N]AMP. All substrates gave significant kinetic isotope effects in a pattern that establishes that the reaction expresses intrinsic kinetic isotope effects in the presence or absence of MgATP. The kinetic isotope effect with [9-15N]AMP decreased from 1.034 +/- 0.002 to 1.021 +/- 0.002 in response to MgATP. The [1'-3H]AMP isotope effect increased from 1.086 +/- 0.003 to 1.094 +/- 0.002, while the kinetic isotope effect for [1',9-14C, 15N]AMP decreased from 1.085 +/- 0.003 to 1.070 +/- 0.004 in response to allosteric activation with MgATP. Kinetic isotope effects with [1'-14C]AMP and [2'-2H]AMP were 1.041 +/- 0.006 and 1.089 +/- 0.002 and were not changed by addition of MgATP.(ABSTRACT TRUNCATED AT 250 WORDS)

The use of importance sampling with the random‐walk method of solving the Schrodinger equation in a way devised by Ceperley is examined in its application to determining the electronic energy of ground state H+3. The improved method yields energies of higher accuracy than prior random‐walk or variational calculations. The required computation effort remains large for high accuracy but might be reduced by improved trial wave functions used in importance sampling. For the equilateral triangle configuration with side length of 1.6500 a.u., the calculated total energy is −1.3439±0.0002 a.u. This value lies below the upper bound of −1.34335 a.u. established in the lowest‐energy variational calculations by Salmon and Poshusta and above their estimate of −1.3447 a.u. as the true value. Energies calculated for four other nuclear configurations of interest in determining the vibrational frequencies of H+3 are found to be, typically, 0.001 to 0.003 a.u. lower than those of the most accurate variational calculations...

The mechanism of acid and enzymatic hydrolysis of the N-glycosidic bond of AMP has been investigated by fitting experimentally observed kinetic isotope effects [Parkin, D. W., & Schramm, V. L. (1987) Biochemistry (preceding paper in this issue)] to calculated kinetic isotope effects for proposed transition-state structures. The sensitivity of the transition-state calculations was tested by "arying the transition-state structure and comparing changes in the calculated kinetic isotope effects with the experimental values of the isotope effect measurements. The kinetic isotope effects for the acid-catalyzed hydrolysis of AMP are best explained by a transition state with considerable oxycarbonium character in the ribose ring, significant bonding remaining to the departing adenine ring, participation of a water nucleophile, and protonation of the adenine ring. A transition-state structure without preassociation of the water nucleophile cannot be eliminated by the data. Enzymatic hydrolysis of the N-glycosidic bond of AMP by AMP nucleosidase from Azotobacter vinelandii was analyzed in the absence and presence of MgATP, the allosteric activator that increases Vmax approximately 200-fold. The transition states for enzyme-catalyzed hydrolysis that best explain the kinetic isotope effects involve early SN1 transition states with significant bond order in the glycosidic bond and protonation of the adenine base. The enzyme enforces participation of an enzyme-bound water molecule, which has weak bonding to C1' in the transition state. Activation of AMP nucleosidase by MgATP causes the bond order of the glycosidic bond in the transition state to increase significantly. Hyperconjugation in the ribosyl group is altered by enzymatic stabilization of the oxycarbonium ion. This change is consistent with the interaction of an amino acid on the enzyme. Together, these changes stabilize a carboxonium-like transition-state complex that occurs earlier in the reaction pathway than in the absence of allosteric activator. In addition to the allosteric changes that alter transition-state structure, the presence of other inductive effects that are unobserved by kinetic isotope measurements is also likely to increase the catalytic rate.

The random walk method for calculating wave functions and energies of molecular systems is investigated in its application to the H3 system in a symmetric linear configuration (R=1.757 a.u.) matching the expected saddle point for the reaction H+H2→H2+H. Four different types of trial wave functions were examined for the importance sampling method used. A product type of wave function explicitly incorporating interelectron distances and having a simple node structure was found optimum. The calculated total energy is −1.6582±0.0003 a.u. which corresponds to a reaction barrier height of 10.2±0.2 kcal/mol. This energy is slightly lower than the upper bound of 10.28 kcal/mol previously established in variational calculations by Liu and 0.5 kcal/mol above Liu’s estimate of 9.68 kcal/mol as the exact value. The value 10.2 kcal/mol lies at the upper extreme of the range of barrier heights compatible with reaction rates measured experimentally. For the linear asymmetric configuration with R=1.41, 4.33 a.u. the calculated energy is 0.6±0.4 kcal/mol below Liu’s value. Further optimization of node structure for the random walk calculations may (or may not) result in lower values.