Rabies virus circulation in a highly diverse bat assemblage from a high-risk area for zoonoses outbreaks in the Brazilian Amazon.

Bats are the second most diverse order of mammals and play a central role in ecosystem dynamics. They are also important reservoirs of potentially zoonotic microorganisms, of which rabies virus is the most lethal among the bat-transmitted zoonotic pathogens. Importantly, recent outbreaks of human rabies have been reported from the Brazilian Amazon. Here we present a survey of bat species and rabies virus (RABV) circulation in a bat assemblage in the Marajó region, northern Brazil. Using data from mist-net captures and bioacoustic sampling, 56 bat species were recorded along the Jacundá River basin over a 10-day expedition in November 2022. For the investigation of RABV, we used the direct fluorescent antibody test (DFAT) and the rapid fluorescent focus inhibition test (RFFIT). In total, 159 bat individuals from 22 species were investigated for RABV. Five adults of the common vampire bat, Desmodus rotundus, showed RABV-specific antibodies in serum samples. Additionally, we report on local residents with injuries caused by D. rotundus bites and the occurrence of colonies of non-hematophagous bats from different species roosting inside human residences. This scenario raises concerns about the risks of new cases of human rabies and other zoonotic diseases associated with bats in the region and highlights the need for epidemiological surveillance and mitigation measures to prevent outbreaks of emerging infectious diseases.

Does ethnicity impact CYP2D6 genotype-phenotype relationships?

Polymorphism of the CYP2D6 gene leads to substantial interindividual variability in CYP2D6 enzyme activity. Despite improvements in prediction of CYP2D6 activity based on genotype information, large interindividual variability within CYP2D6 genotypes remains and ethnicity could be a contributing factor. The aim of this study was to investigate interethnic differences in CYP2D6 activity using clinical datasets of three CYP2D6 substrates: (i) brexpiprazole (N = 476), (ii) tedatioxetine (N = 500), and (iii) vortioxetine (N = 1073). The CYP2D6 activity of all individuals in the dataset was estimated through population pharmacokinetic analyses as previously reported. Individuals were assigned a CYP2D6 phenotype and CYP2D6 genotype group based on their CYP2D6 genotype and interethnic differences were investigated within each group. Among individuals categorized as CYP2D6 normal metabolizers, African Americans had a lower CYP2D6 activity compared to Asians (p < 0.01) and in the tedatioxetine and vortioxetine analyses also compared to Whites (p < 0.01). Among CYP2D6 intermediate metabolizers, interethnic differences were also observed, but the findings were not consistent across the substrates. Asian carriers of CYP2D6 decreased function alleles tended to exhibit higher CYP2D6 activity compared to Whites and African Americans. The observed interethnic differences within the CYP2D6 phenotype and genotype groups appeared to be driven by differences in CYP2D6 allele frequencies across ethnicities rather than interethnic differences in enzyme activity for individuals carrying identical CYP2D6 genotypes.

The Michigan Genomics Initiative: A biobank linking genotypes and electronic clinical records in Michigan Medicine patients.

Biobanks of linked clinical patient histories and biological samples are an efficient strategy to generate large cohorts for modern genetics research. Biobank recruitment varies by factors such as geographic catchment and sampling strategy, which affect biobank demographics and research utility. Here, we describe the Michigan Genomics Initiative (MGI), a single-health-system biobank currently consisting of >91,000 participants recruited primarily during surgical encounters at Michigan Medicine. The surgical enrollment results in a biobank enriched for many diseases and ideally suited for a disease genetics cohort. Compared with the much larger population-based UK Biobank, MGI has higher prevalence for nearly all diagnosis-code-based phenotypes and larger absolute case counts for many phenotypes. Genome-wide association study (GWAS) results replicate known findings, thereby validating the genetic and clinical data. Our results illustrate that opportunistic biobank sampling within single health systems provides a unique and complementary resource for exploring the genetics of complex diseases.

Estimating the In Vivo Function of CYP2D6 Alleles through Population Pharmacokinetic Modeling of Brexpiprazole.

Accurate prediction of CYP2D6 phenotype from genotype information is important to support safe and efficacious pharmacotherapy with CYP2D6 substrates. To facilitate accurate CYP2D6 genotype-phenotype translation, there remains a need to investigate the enzyme activity associated with individual CYP2D6 alleles using large clinical data sets. This study aimed to quantify and compare the in vivo function of different CYP2D6 alleles through population pharmacokinetic (PopPK) modeling of brexpiprazole using data from 13 clinical studies. A PopPK model of brexpiprazole and its two metabolites, DM-3411 and DM-3412, was developed based on plasma concentration samples from 826 individuals. As the minor metabolite, DM-3412, is formed via CYP2D6, the metabolic ratio of DM-3412:brexpiprazole calculated from the PopPK parameter estimates was used as a surrogate measure of CYP2D6 activity. A CYP2D6 genotype-phenotype analysis based on 496 subjects showed that the CYP2D6*2 allele (n = 183) was associated with only 10% enzyme activity relative to the wild-type allele (CYP2D6*1) and a low enzyme activity was consistently observed across genotypes containing CYP2D6*2. Among the decreased function alleles, the following enzyme activities relative to CYP2D6*1 were estimated: 23% for CYP2D6*9 (n = 20), 32% for CYP2D6*10 (n = 62), 64% for CYP2D6*14 (n = 1), 4% for CYP2D6*17 (n = 37), 4% for CYP2D6*29 (n = 13), and 9% for CYP2D6*41 (n = 64). These findings imply that a lower functional value would more accurately reflect the in vivo function of many reduced function CYP2D6 alleles in the metabolism of brexpiprazole. The low enzyme activity observed for CYP2D6*2, which has also been reported by others, suggests that the allele exhibits substrate-specific enzyme activity.

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

Medium- and large-sized mammals from Estação Biológica Fiocruz Mata Atlântica, Rio de Janeiro, south-eastern Brazil.

The Pedra Branca Forest is in a highly urbanised region of the central portion of Rio de Janeiro City and comprises the largest urban forest in the world (> 12,000 ha). The local flora and fauna are protected by three conservation units and the Estação Biológica Fiocruz Mata Atlântica (EFMA), which comprises 462 hectares on the east side of the remnant. The local biodiversity is still little known compared to other Atlantic Forest remnants from the Rio de Janeiro State. Here, we provide results of a survey of medium- and large-sized terrestrial mammals from the EFMA. In addition, we analysed the distribution of this fauna along three habitat types defined as Peridomicile, Transitional Forest and Forest Core. Sampling was performed from 2017 to 2020 and comprised a camera-trap survey, interviews with residents and local workers and occasional records. Results include occurrence records for 16 autochthonous and one allochthonous (Callithrix sp.) wild mammals, which are distributed into 14 families and seven orders, in addition to the presence of free-ranging domestic dogs and cats. Four species are in some category of threat of extinction at national or global levels. Amongst them, Leontopithecusrosalia (first record for the Rio de Janeiro City in more than a century) and Leopardusguttulus are classified as Vulnerable by IUCN. Most wild native species were registered in the three habitat types, but with differences in the frequency of records. Our results indicate that the presence of domestic dogs and cats influenced the species composition in each area, with Nasuanasua, Dasyproctaleporina and Didelphisaurita less frequent in places where domestic dogs and cats are more frequent. This is the first systematic effort to understand the occurrence and distribution of mid- and large-sized mammals in the Pedra Branca Forest.

An open approach to systematically prioritize causal variants and genes at all published human GWAS trait-associated loci.

Genome-wide association studies (GWASs) have identified many variants associated with complex traits, but identifying the causal gene(s) is a major challenge. In the present study, we present an open resource that provides systematic fine mapping and gene prioritization across 133,441 published human GWAS loci. We integrate genetics (GWAS Catalog and UK Biobank) with transcriptomic, proteomic and epigenomic data, including systematic disease-disease and disease-molecular trait colocalization results across 92 cell types and tissues. We identify 729 loci fine mapped to a single-coding causal variant and colocalized with a single gene. We trained a machine-learning model using the fine-mapped genetics and functional genomics data and 445 gold-standard curated GWAS loci to distinguish causal genes from neighboring genes, outperforming a naive distance-based model. Our prioritized genes were enriched for known approved drug targets (odds ratio = 8.1, 95% confidence interval = 5.7, 11.5). These results are publicly available through a web portal ( http://genetics.opentargets.org ), enabling users to easily prioritize genes at disease-associated loci and assess their potential as drug targets.

Cytochrome P450 2D6 genotype-phenotype characterization through population pharmacokinetic modeling of tedatioxetine.

The cytochrome P450 (CYP) 2D6 enzyme exhibits large interindividual differences in metabolic activity. Patients are commonly assigned a CYP2D6 phenotype based on their CYP2D6 genotype, but there is a lack of consensus on how to translate genotypes into phenotypes, causing inconsistency in genotype-based dose recommendations. The aim of this study was to quantify and compare the impact of different CYP2D6 genotypes and alleles on CYP2D6 metabolism using a large clinical data set. A population pharmacokinetic (popPK) model of tedatioxetine and its CYP2D6-dependent metabolite was developed based on pharmacokinetic data from 578 subjects. The CYP2D6-mediated metabolism was quantified for each subject based on estimates from the final popPK model, and CYP2D6 activity scores were calculated for each allele using multiple linear regression. The activity scores estimated for the decreased function alleles were 0.46 (CYP2D6*9), 0.34 (CYP2D6*10), 0.01 (CYP2D6*17), 0.65 (CYP2D6*29), and 0.21 (CYP2D6*41). The CYP2D6*17 and CYP2D6*41 alleles were thus associated with the lowest CYP2D6 activity, although only the difference to the CYP2D6*9 allele was shown to be statistically significant (p = 0.02 and p = 0.05, respectively). The study provides new in vivo evidence of the enzyme function of different CYP2D6 genotypes and alleles. Our findings suggest that the activity score assigned to CYP2D6*41 should be revisited, whereas CYP2D6*17 appears to exhibit substrate-specific behavior. Further studies are needed to confirm the findings and to improve the understanding of CYP2D6 genotype-phenotype relationships across substrates.

Quantification of In Vivo Metabolic Activity of CYP2D6 Genotypes and Alleles Through Population Pharmacokinetic Analysis of Vortioxetine.

Assignment of CYP2D6 phenotype from genotype data can be challenging and despite efforts to standardize translation, there is currently no universally accepted method. To facilitate standardization, there remains a need to precisely quantify the in vivo function of different CYP2D6 genotypes. Vortioxetine is metabolized to its major metabolite, Lu AA34443, primarily via CYP2D6. The aim of this study was to quantify the in vivo CYP2D6 activity of different CYP2D6 alleles and genotypes through population pharmacokinetic (PopPK) modeling of vortioxetine and Lu AA34443. Plasma concentration data of vortioxetine and Lu AA34443 from 1,140 subjects originating from 29 clinical pharmacology studies were pooled for the analysis. A joint PopPK model described the pharmacokinetics of vortioxetine and Lu AA34443 simultaneously and provided estimates of the CYP2D6-mediated metabolism for each subject. Subjects normally classified as CYP2D6 intermediate metabolizers (IMs) showed different levels of CYP2D6 activity with carriers of one fully functional allele and one null function allele having 77% higher CYP2D6 activity compared with carriers of two decreased function alleles (P < 0.0001). The decreased function alleles were associated with different levels of reduction of CYP2D6 activity. Fixing the activity of fully functional alleles to 1.0, the relative activities of CYP2D6*9, CYP2D6*10, CYP2D6*17, and CYP2D6*41 were 0.22, 0.37, 0.17, and 0.21, respectively. The activity of CYP2D6*10 was shown to be significantly greater than that of CYP2D6*17 (P = 0.01) and CYP2D6*41 (P = 0.02). These results warrant further discussion of current CYP2D6 genotype-phenotype classification systems particularly regarding decreased function alleles and the IM phenotype.

Open Targets Genetics: systematic identification of trait-associated genes using large-scale genetics and functional genomics.

Open Targets Genetics (https://genetics.opentargets.org) is an open-access integrative resource that aggregates human GWAS and functional genomics data including gene expression, protein abundance, chromatin interaction and conformation data from a wide range of cell types and tissues to make robust connections between GWAS-associated loci, variants and likely causal genes. This enables systematic identification and prioritisation of likely causal variants and genes across all published trait-associated loci. In this paper, we describe the public resources we aggregate, the technology and analyses we use, and the functionality that the portal offers. Open Targets Genetics can be searched by variant, gene or study/phenotype. It offers tools that enable users to prioritise causal variants and genes at disease-associated loci and access systematic cross-disease and disease-molecular trait colocalization analysis across 92 cell types and tissues including the eQTL Catalogue. Data visualizations such as Manhattan-like plots, regional plots, credible sets overlap between studies and PheWAS plots enable users to explore GWAS signals in depth. The integrated data is made available through the web portal, for bulk download and via a GraphQL API, and the software is open source. Applications of this integrated data include identification of novel targets for drug discovery and drug repurposing.

LabWAS: Novel findings and study design recommendations from a meta-analysis of clinical labs in two independent biobanks.

Phenotypes extracted from Electronic Health Records (EHRs) are increasingly prevalent in genetic studies. EHRs contain hundreds of distinct clinical laboratory test results, providing a trove of health data beyond diagnoses. Such lab data is complex and lacks a ubiquitous coding scheme, making it more challenging than diagnosis data. Here we describe the first large-scale cross-health system genome-wide association study (GWAS) of EHR-based quantitative laboratory-derived phenotypes. We meta-analyzed 70 lab traits matched between the BioVU cohort from the Vanderbilt University Health System and the Michigan Genomics Initiative (MGI) cohort from Michigan Medicine. We show high replication of known association for these traits, validating EHR-based measurements as high-quality phenotypes for genetic analysis. Notably, our analysis provides the first replication for 699 previous GWAS associations across 46 different traits. We discovered 31 novel associations at genome-wide significance for 22 distinct traits, including the first reported associations for two lab-based traits. We replicated 22 of these novel associations in an independent tranche of BioVU samples. The summary statistics for all association tests are freely available to benefit other researchers. Finally, we performed mirrored analyses in BioVU and MGI to assess competing analytic practices for EHR lab traits. We find that using the mean of all available lab measurements provides a robust summary value, but alternate summarizations can improve power in certain circumstances. This study provides a proof-of-principle for cross health system GWAS and is a framework for future studies of quantitative EHR lab traits.

Utility of plasma neurofilament light and total tau for clinical trials in Alzheimer's disease.

INTRODUCTION: Several blood-based biomarkers are associated with neuronal injury, but their utility in interventional clinical trials is unclear. This study retrospectively evaluated the utility of plasma neurofilament light (NfL) and total tau (t-tau) in an 18-month trial in mild Alzheimer's disease (AD). METHODS: Correlation and conditional independence analyses and Gaussian graphical models were used to investigate cross-sectional and longitudinal relations between NfL, t-tau, and clinical scales. RESULTS: NfL had a stronger association than t-tau with clinical scales; t-tau did not hold additional information to that given by NfL (P > 0.05 at all time points). NfL held independent information about shorter-term (3- to 6-month) progression beyond patient age and clinical scores. However, no meaningful gain in power was found when adjusting a longitudinal analysis of cognitive scores for baseline NfL. DISCUSSION: Plasma NfL is superior to t-tau in mild AD. The ability of NfL to detect changes before clinical manifestations makes it a promising biomarker of drug response in trials of disease-modifying drugs.

Chromosome 1q21.2 and additional loci influence risk of spontaneous coronary artery dissection and myocardial infarction.

Spontaneous coronary artery dissection (SCAD) is a non-atherosclerotic cause of myocardial infarction (MI), typically in young women. We undertook a genome-wide association study of SCAD (Ncases = 270/Ncontrols = 5,263) and identified and replicated an association of rs12740679 at chromosome 1q21.2 (Pdiscovery+replication = 2.19 × 10-12, OR = 1.8) influencing ADAMTSL4 expression. Meta-analysis of discovery and replication samples identified associations with P < 5 × 10-8 at chromosome 6p24.1 in PHACTR1, chromosome 12q13.3 in LRP1, and in females-only, at chromosome 21q22.11 near LINC00310. A polygenic risk score for SCAD was associated with (1) higher risk of SCAD in individuals with fibromuscular dysplasia (P = 0.021, OR = 1.82 [95% CI: 1.09-3.02]) and (2) lower risk of atherosclerotic coronary artery disease and MI in the UK Biobank (P = 1.28 × 10-17, HR = 0.91 [95% CI :0.89-0.93], for MI) and Million Veteran Program (P = 9.33 × 10-36, OR = 0.95 [95% CI: 0.94-0.96], for CAD; P = 3.35 × 10-6, OR = 0.96 [95% CI: 0.95-0.98] for MI). Here we report that SCAD-related MI and atherosclerotic MI exist at opposite ends of a genetic risk spectrum, inciting MI with disparate underlying vascular biology.

Genes for Good: Engaging the Public in Genetics Research via Social Media.

The Genes for Good study uses social media to engage a large, diverse participant pool in genetics research and education. Health history and daily tracking surveys are administered through a Facebook application, and participants who complete a minimum number of surveys are mailed a saliva sample kit ("spit kit") to collect DNA for genotyping. As of March 2019, we engaged >80,000 individuals, sent spit kits to >32,000 individuals who met minimum participation requirements, and collected >27,000 spit kits. Participants come from all 50 states and include a diversity of ancestral backgrounds. Rates of important chronic health indicators are consistent with those estimated for the general U.S. population using more traditional study designs. However, our sample is younger and contains a greater percentage of females than the general population. As one means of verifying data quality, we have replicated genome-wide association studies (GWASs) for exemplar traits, such as asthma, diabetes, body mass index (BMI), and pigmentation. The flexible framework of the web application makes it relatively simple to add new questionnaires and for other researchers to collaborate. We anticipate that the study sample will continue to grow and that future analyses may further capitalize on the strengths of the longitudinal data in combination with genetic information.

Clinical Implications of Identifying Pathogenic Variants in Individuals With Thoracic Aortic Dissection.

BACKGROUND: Thoracic aortic dissection is an emergent life-threatening condition. Routine screening for genetic variants causing thoracic aortic dissection is not currently performed for patients or family members. METHODS: We performed whole exome sequencing of 240 patients with thoracic aortic dissection (n=235) or rupture (n=5) and 258 controls matched for age, sex, and ancestry. Blinded to case-control status, we annotated variants in 11 genes for pathogenicity. RESULTS: Twenty-four pathogenic variants in 6 genes (COL3A1, FBN1, LOX, PRKG1, SMAD3, and TGFBR2) were identified in 26 individuals, representing 10.8% of aortic cases and 0% of controls. Among dissection cases, we compared those with pathogenic variants to those without and found that pathogenic variant carriers had significantly earlier onset of dissection (41 versus 57 years), higher rates of root aneurysm (54% versus 30%), less hypertension (15% versus 57%), lower rates of smoking (19% versus 45%), and greater incidence of aortic disease in family members. Multivariable logistic regression showed that pathogenic variant carrier status was significantly associated with age <50 (odds ratio [OR], 5.5; 95% CI, 1.6-19.7), no history of hypertension (OR, 5.6; 95% CI, 1.4-22.3), and family history of aortic disease (mother: OR, 5.7; 95% CI, 1.4-22.3, siblings: OR, 5.1; 95% CI, 1.1-23.9, children: OR, 6.0; 95% CI, 1.4-26.7). CONCLUSIONS: Clinical genetic testing of known hereditary thoracic aortic dissection genes should be considered in patients with a thoracic aortic dissection, followed by cascade screening of family members, especially in patients with age-of-onset <50 years, family history of thoracic aortic disease, and no history of hypertension.

Publisher Correction: Genome-wide association study of delay discounting in 23,217 adult research participants of European ancestry.

The author list was in the wrong order in the HTML version of the original article and in the HTML version of the original correction notice. This has been corrected to show the 23andMe Research Team as the fourth author and Abraham A. Palmer as the last author in both places.

Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps.

We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency <5%, 14 with estimated allelic odds ratio >2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).

Biobank-driven genomic discovery yields new insight into atrial fibrillation biology.

To identify genetic variation underlying atrial fibrillation, the most common cardiac arrhythmia, we performed a genome-wide association study of >1,000,000 people, including 60,620 atrial fibrillation cases and 970,216 controls. We identified 142 independent risk variants at 111 loci and prioritized 151 functional candidate genes likely to be involved in atrial fibrillation. Many of the identified risk variants fall near genes where more deleterious mutations have been reported to cause serious heart defects in humans (GATA4, MYH6, NKX2-5, PITX2, TBX5)1, or near genes important for striated muscle function and integrity (for example, CFL2, MYH7, PKP2, RBM20, SGCG, SSPN). Pathway and functional enrichment analyses also suggested that many of the putative atrial fibrillation genes act via cardiac structural remodeling, potentially in the form of an 'atrial cardiomyopathy'2, either during fetal heart development or as a response to stress in the adult heart.