bluuebunny/crossref_metadata_2025_split huggingface dataset:
Loci on chromosome 12q13.2 encompassing ERBB3, PA2G4 and RAB5B are associated with polycystic ovary syndrome
Authors: Harris R. Alan , Archer Kellie J. , Goodarzi Mark O. , York Timothy P. , Rogers Jeffrey , Dunaif Andrea , McAllister Jan , Strauss Jerome F 
Published: May 2022

AbstractPolycystic ovary syndrome (PCOS) is characterized by hyperandrogenemia of ovarian theca cell origin. Here we report the significant association of 15 single nucleotide polymorphisms (SNPs), identified by whole exome sequencing (WES). DNA was isolated from well-characterized theca cell preparations from women of European ancestry with PCOS (N=9) and elevated androgen production in vitro and from normal ovulatory women (N=7). Of the SNPs, 10 are located within 150 kb on chromosome 12q13.2. This region contains three plausible PCOS candidate genes (ERBB3/PA2G4/RAB5B), two of which (ERBB3 and RAB5B) have been identified in GWAS of PCOS. None of the SNPs individually had a significant association with PCOS or in vivo androgen levels when evaluated in an independent cohort (n=318) of families with one or more daughters with PCOS, but a haplotype consisting of the minor alleles of three of the SNPS (rs773121, rs773123 and rs812826) was found preferentially in women with PCOS and elevated androgen levels (p=0.0583). Moreover, the three minor alleles in this haplotype were significantly associated with anti-Mullerian Hormone (AMH) levels, a marker of follicular reserve and follicular maturation. Two of the three SNP minor alleles are predicted to have significant functional consequences (rs773123 a missense SNP in ERBB3, and rs812826, a SNP in the PA2G4 promoter). Notably, PA2G4 encodes a protein that interacts with the ERBB3 cytoplasmic domain, which is also the domain where the missense variant resides. These findings provide support for the contribution and probable functional significance of loci on chromosome 12q13.2 to the pathophysiology underlying PCOS.Author SummaryPolycystic ovary syndrome (PCOS) is the most common endocrine disorder of women of reproductive age. We identified 15 single nucleotide polymorphisms (SNPs) associated with androgen production in theca cells from normal ovulatory women and women with PCOS. Of these SNPs, 10 are within a 150 kbp region of chromosome 12 including 9 that form a haplotype. This region contains three PCOS candidate genes (ERBB3/PA2G4/RAB5B). These SNPs were further examined in an independent cohort of families with one or more daughters with PCOS. A haplotype consisting of the minor alleles of three of the SNPS was found preferentially in women with PCOS. Furthermore, the three minor alleles in this haplotype were significantly associated with anti-Mullerian Hormone (AMH) levels, a marker of follicular reserve and maturation. Two SNPs in the chromosome 12 haplotype were likely to have functional consequences based on genomic context, suggesting that they affect ERBB3 and PA2G4 interactions or PA2G4 expression.
Autism spectrum disorders and brain volume link through a set of mTOR-related genes
Authors: Arenella Martina , Mota Nina R. , Teunissen Mariel W.A. , Brunner Han G. , Bralten Janita 
Published: May 2022

AbstractBackgroundLarger than average head and brain sizes are often observed in individuals with Autism Spectrum Disorders (ASDs). ASDs and brain volume are both highly heritable, with multiple genetic variants contributing. However, it is unclear whether ASDs and brain volume share any genetic mechanisms. Genes from the mammalian target of rapamycin (mTOR) pathway influence brain volume, and variants are found in rare genetic syndromes that include autism spectrum disorder features. Here we investigated whether variants in mTOR-related genes are also associated with ASDs and if they constitute a genetic link between large brains and ASDs.MethodsWe extended our analyses between large heads (macrocephaly) and rare de novo mTOR-related variants in an intellectual disability cohort (N=2,258). Subsequently using Fisher’s exact tests we investigated the co-occurrence of mTOR-related de novo variants and ASDs in the denovo-db database (N=23,098). We next selected common genetic variants within a set of 96 mTOR-related genes in genome-wide genetic association data of ASDs (N=46,350) to test gene-set association using MAGMA. Lastly, we tested genetic correlation between genome-wide genetic association data of ASDs (N=46,350) and intracranial volume (N=25,974) globally using LD-score regression as well as mTOR-specific by restricting the genetic correlation to the mTOR-related genes using GNOVA.ResultsOur results show that both macrocephaly and ASDs occur above chance-level in individuals carrying rare de novo variants in mTOR-related genes. We found a significant mTOR gene-set association with ASDs (p=0.0029) and an mTOR-stratified positive genetic correlation between ASDs and intracranial volume (p=0.027), despite the absence of a significant genome-wide correlation (p=0.81).ConclusionsThis work indicates that both rare and common variants in mTOR-related genes are associated with brain volume and ASDs and genetically correlate them in the expected direction. We demonstrate that genes involved in mTOR signalling are potential mediators of the relationship between having a large brain and having ASDs.
Accurate Screening for Early-Stage Breast Cancer by Detection and Profiling of Circulating Tumor Cells
Authors: Crook Timothy , Patil Darshana , Akolkar Dadasaheb , Ranade Anantbhushan , Limaye Sewanti , Page Raymond , Datta Vineet , Fulmali Pradip , Apurwa Sachin , Schuster Stefan , Srinivasan Ajay , Datar Rajan 
Published: May 2022

ABSTRACTBACKGROUNDScreening of asymptomatic women for early detection of Breast Cancer (BrC) is associated with improved survival. Presently, mammography is the standard of care (SoC) for BrC screening but has lower accuracy for invasive cancers as well as in women with higher breast tissue density.METHODSIn this manuscript, we describe an accurate blood-based breast cancer detection test based on functional enrichment of breast adenocarcinoma associated circulating tumor cells (BrAD-CTCs) and their identification via multiplexed fluorescence immunocytochemistry (ICC) profiling for GCDFP15, GATA3, EpCAM, PanCK and CD45 status.RESULTSThe test accurately detects BrAD-CTCs in breast cancers irrespective of age, ethnicity, disease stage, grade and hormone receptor status. Analytical validation established the high accuracy and reliability of the test under intended use conditions. A case-control study with samples from 9,632 healthy women and 548 known BrC cases established 100% specificity and 92.07% overall sensitivity; stage-wise sensitivities were 70.00% for Stage 0, 89.36% for Stage I, 95.74% for Stage II and 100% for Stage III and Stage IV cancers. In a prospective clinical study with 141 suspected cases of breast cancer who underwent a biopsy after blood collection, the test showed 93.1% specificity and 94.64% overall sensitivity in differentiating breast cancer cases (n = 112) from those with benign breast conditions (n = 29); stage-wise sensitivities were 87.50% for Stage 0, 95.83% for Stage I and Stage II, 95.00% for Stage III and 100% for Stage IV cancers.CONCLUSIONThe findings reported in this manuscript support the clinical potential of this test for blood based BrC detection.
Development and evaluation of an interoperable natural language processing system for identifying pneumonia across clinical settings of care
Authors: Chapman Alec B , Peterson Kelly S , Rutter Elizabeth , Nevers McKenna , Zhang Mingyuan , Ying Jian , Jones Makoto , Classen David , Jones Barbara 
Published: May 2022

ABSTRACTObjectiveTo evaluate the feasibility, accuracy, and interoperability of a natural language processing (NLP) system which extracts diagnostic assertions of pneumonia in different clinical notes and institutions.Materials and MethodsAn NLP system was designed to identify assertions of pneumonia in three types of clinical notes from electronic health records (EHRs): emergency department notes, radiology reports, and discharge summaries. The lexicon and classification logic were tailored for each note type. The system was first developed and evaluated using annotated notes from the Department of Veterans Affairs. Interoperability was assessed using data from the University of Utah.ResultsThe NLP system was comprised of 782 rules and achieved moderate-to-high performance in all three note types in VA (precision/recall/f1: emergency=88.1/86.0/87.1; radiology=71.4/96.2/82.0; discharge=88.3/93.0/90.1). When applied to UU data, performance was maintained in emergency and radiology but decreased in discharge summaries (emergency=84.7/94.3/89.3; radiology=79.7/100.0/87.9; discharge=65.5/92.7/76.8). Customization with 34 additional rules increased performance for all note types (emergency=89.3/94.3/91.7; radiology=87.0/100.0/93.1; discharge=75.0/95.1/83.4).ConclusionNLP can be used to accurately identify the diagnosis of pneumonia in different clinical settings and institutions. A limited amount of customization to account for differences in lexicon, clinical definition of pneumonia, and EHR structure can achieve high accuracy without substantial modification.
Influencing factors of Anti-SARS-CoV-2-Spike IgG antibody titres in healthcare workers – A cross-section study
Authors: Reusch Julia , Wagenhäuser Isabell , Gabel Alexander , Eggestein Annika , Höhn Anna , Lâm Thiên-Trí , Frey Anna , Schubert-Unkmeir Alexandra , Dölken Lars , Frantz Stefan , Kurzai Oliver , Vogel Ulrich , Krone Manuel , Petri Nils 
Published: May 2022

ABSTRACTBackgroundAgainst the background of the current COVID-19 infection dynamics with the rapid spread of SARS-CoV-2 variants of concern (VOC), above all the Omicron VOC, the immunity of healthcare workers (HCWs) against SARS-CoV-2 continues to be of high importance. Vaccination plays a central role in reducing the severity and potentially the spread of the disease. In healthcare, this is important to prevent disease-related staff shortages. However, there is a lack of data on factors influencing the humoral immune response.AimThe aim of our study was to determine factors influencing the level of Anti-SARS-CoV-2-Spike IgG after SARS-CoV-2 infection or vaccination in healthcare workers.Methods1,750 study participants were recruited who met the following inclusion criteria: age ≥ 18 years, PCR-confirmed SARS-CoV-2 infection and/or at least one dose of COVID-19 vaccination, working in health care. Anti-SARS-CoV-2-Spike IgG titres were determined by SERION ELISA agile SARS-CoV-2 IgG.ResultsMean Anti-SARS-CoV-2-Spike IgG levels increased significantly with the number of COVID-19 vaccinations (92.2 BAU/ml for single dose, 140.9 BAU/ml for two doses and 1,144.3 BAU/ml after threefold vaccination). Hybrid COVID-19 immunized respondents (after infection and vaccination) had significantly higher antibody titres compared with participants after infection only (525.4 BAU/ml vs. 105.7 BAU/ml). Anti-SARS-CoV-2-Spike IgG titres declined significantly with time after administration of the second vaccine dose. Smoking and high age were associated with lower titres.ConclusionBoth recovered and vaccinated HCWs presented a predominantly good humoral immune response with decreasing antibody levels over the temporal course. Smoking and higher age limited the humoral SARS-CoV-2 immunity. This reduced immune response is an important aspect as people with these risk factors are recognized as people with an increased risk for a severe course of disease.
Performance of Existing and Novel Symptom- and Antigen Testing-Based COVID-19 Case Definitions in a Community Setting
Authors: Lee Scott , Almendares Olivia , Prince-Guerra Jessica L. , Heilig Charles M. , Tate Jacqueline E. , Kirking Hannah L. 
Published: May 2022

AbstractPoint-of-care antigen tests are an important tool for SARS-CoV-2 detection, but they are less clinically sensitive than real-time reverse-transcription PCR (RT-PCR), impacting their efficacy as screening procedures. Our goal in this study was to see whether we could improve this sensitivity by considering antigen test results in combination with other relevant information, namely exposure status and reported symptoms. In November of 2020, we collected 3,419 paired upper respiratory specimens tested by RT-PCR and the Abbott BinaxNOW antigen test at two community testing sites in Pima County, Arizona. We used symptom, exposure, and antigen testing data to evaluate the sensitivity and specificity of various symptom definitions in predicting RT-PCR positivity. Our analysis yielded 6 novel multi-symptom case definitions with and without antigen test results, the best of which overall achieved a Youden’s J index of 0.66, as compared with 0.52 for antigen testing alone. Using a random forest as a guide, we show that this definition, along with our others, does not lose the ability to generalize well to new data despite achieving optimal performance in our sample. Our methodology is broadly applicable, and we have made our code publicly available to aid public health practitioners in developing or fine- tuning their own screening rules.
Associations between recreational cannabis legalization and cannabis-related emergency department visits by age, gender, and geographic status in Ontario, Canada: an interrupted time series study
Authors: Kim Chungah , Chum Antony , Nielsen Andrew , Allin Sara , Penny Tara , Rittenbach Katherine , MacMaster Frank P. , O’Campo Patricia 
Published: May 2022

ABSTRACTLegalization of recreational cannabis in Ontario included the legalization of flower and herbs (Phase 1, October 2018), and was followed by the deregulation of cannabis retailers and sales of edibles (Phase 2, February 2020). Research on the impact of cannabis legalization on acute care utilization is nascet; no research has investigated potential age, gender, and geographically vulnerable subgroup effects. Residents living in Northern Ontario not only have higher levels of substance use problems, but also have inadequate access to primary healthcare. Our study investigated the impact of Ontario’s recreational cannabis policy (including Phase 1 and 2) on cannabis-attributable emergency department (ED) visits, and estimated the impact separately for different age and gender groups, with additional analyses focused on Northern Ontarians. We created a cohort of adults (18 and over) eligible for provincial universal health insurance with continuous coverage from 2015-2021 (n=14,900,820). An interrupted time-series was used to examine the immediate impact and month-to-month changes in cannabis-related ED visits associated with Phase 1 & 2 for each subgroup. While Northern Ontario has higher rates of cannabis-related ED visits, both Northern and Southern Ontario show similar patterns of changes. Phase 1 was associated with significant increases in adults 25-64, with the strongest increases seen in women 45-64. Month-to-month trends were flattened in most groups compared to pre-legalisation. Phase 2 was associated with significant immediate increases for adults aged 18-44 in both genders, but the increases were larger in women than men. No significant month-to-month changes were detected in this period. While current preventive efforts are largely focused on reducing cannabis-related harms in youths and younger adults, our results show that adults 25-64, particularly women, have been significantly impacted by cannabis policies. Further research on gender-specific cannabis dosage and targeted interventions for adult women should be investigated. Legalization did not appear to have a differential impact on Northern versus Southern Ontario, but higher rates of ED visits in the North should be addressed.
A Phase1 Results of a Non-Stabilized Spike-Encoding mRNA Vaccine in Adults
Authors: Gatechompol Sivaporn , Kittanamongkolchai Wonngarm , Ketloy Chutitorn , Prompetchara Eakachai , Thitithanyanont Arunee , Jongkaewwattana Anan , Buranapraditkun Supranee , Alameh Mohamad-Gabriel , Ubolyam Sasiwimol , Sophonphan Jiratchaya , Apornpong Tanakorn , Kerr Stephen , Kamarulzaman Adeeba , Siwamogsatham Sarawut , Kroon Eugène , Puthanakit Thanyawee , Patarakul Kanitha , Palaga Tanapat , Wijagkanalan Wassana , Weissman Drew , Ruxrungtham Kiat ,   ChulaVAC-001 study team
Published: May 2022

ABSTRACTBackgroundEffective COVID-19 mRNA vaccines are mainly available in high-income countries. ChulaCov19, a prefusion non-stabilized Spike protein-encoding, nucleoside-modified mRNA, lipid nanoparticle encapsulated vaccine development, aims to enhance accessibility of mRNA vaccine and future pandemic preparedness for low- to middle-income countries.MethodsSeventy-two eligible volunteers, 36 aged 18-55 (adults) followed by 36 aged 56-75 (elderly) enrolled in a dose escalation study of ChulaCov19 mRNA vaccine. Two doses of vaccine were given 21 days apart at 10, 25, or 50 µg/dose (12/group). Safety was the primary and immunogenicity the secondary outcome. Human convalescents’ (HCS) and Pfizer/BioNTech vaccinees’ sera provided comparison panels.ResultsAll three doses of ChulaCov19 were well tolerated and elicited robust dose-dependent and age- dependent B- and T-cell responses. Transient mild/moderate injection site pain, fever, chills, fatigue, and headache were more common after the second dose. Four weeks after the second ChulaCov19: dose at 10, 25, and 50 µg dose, MicroVNT-50 Geometric mean titer (GMT) against wild-type was 848, 736 and 1,140 IU/mL, respectively, versus 267 IU/mL for HCS. All dose levels elicited 100% seroconversion, with GMT ratio 4-8-fold higher than for HCS (p<0.01), and high IFNγ spot-forming cells/million peripheral blood mononuclear cells. The 50 µg dose induced better cross-neutralization against Alpha, Beta, Gamma, and Delta variants than lower doses.ConclusionsChulaCov19 at 50 µg/dose is well tolerated and elicited higher neutralizing antibodies than HCS with strong T-cell responses. These antibodies cross neutralized four variants of concern and ChulaCov19 has therefore proceeded to phase 2 and 3 clinical trials.Trial registration numberClinicalTrials.gov Identifier NCT04566276Graphical Abstract
Latent class analysis identifies distinctive behavioral subtypes in children with fragile X syndrome
Authors: Kaufmann Walter E. , Raspa Melissa , Bann Carla M. , Gable Julia M. , Harris Holly K. , Budimirovic Dejan B. , Lozano Reymundo ,   FORWARD Consortium
Published: May 2022

AbstractFragile X syndrome (FXS) is associated with a characteristic profile of physical and neurobehavioral abnormalities. These phenotypical features are highly variable among affected individuals, which leads to difficulties in developing and evaluating treatments as well as in determining accurate prognosis. The current investigation employed data from FORWARD, a clinic-based natural history study of FXS, to identify subtypes by applying latent class analysis (LCA).A pediatric cross-sectional sample of 1,072 males and 338 females was subjected to LCA to identify neurobehavioral classes (groups). Input consisted of multiple categorical and continuous cognitive and behavioral variables, including co-occurring behavioral conditions, sleep and sensory problems, measures of autistic behavior (SCQ, SRS-2), and scores on the Aberrant Behavior Checklist revised for FXS (ABCFX). Clinically relevant class solutions were further delineated by identifying predictors using stepwise logistic regressions and pairwise comparisons. Following this, classes were characterized in terms of key demographic, genetic, and clinical parameters.LCA fit parameters supported 2- to 6-class models, which showed good correspondence between patterns of co-occurring conditions and scores on standardized measures. The 5-class solution yielded the most clinically meaningful characterization of groups with unique cognitive and behavioral profiles. The “Mild” class (31%) included patients with attention problems and anxiety but few other major behavioral challenges as reflected by scale scores. Most individuals in the “Severe” class (9%) exhibited multiple co-occurring conditions and high mean scale scores on behavioral measures. Three “Moderate” classes were identified: a “Moderate Behavior” class (32%), a “Social Impairment” class (7%), and a “Disruptive Behavior” class (20%). All classes displayed distinctive SRS-2, SCQ, and ABCFX profiles, which reflected their degree of non-overlap as estimated by pairwise effect sizes. Groups differed with regard to sex, intellectual disability, autism spectrum disorder diagnosis, and medication use.These findings support the notion that, it is possible to identify behavioral subtypes in children with FXS, reflecting both overall level of severity and specific areas of impairment. These subtypes have implications for clinical management and therapeutic development and assessment. Future studies are needed to determine the stability of these group profiles and their relationship with other aspects of the FXS phenotype.
Optimality of Maximal-Effort Vaccination
Authors: Penn Matthew J. , Donnelly Christl A. 
Published: May 2022

AbstractIt is widely acknowledged that vaccinating at maximal effort in the face of an ongoing epidemic is the best strategy to minimise infections and deaths from the disease. Despite this, no one has proved that this is guaranteed to be true if the disease follows multi-group SIR (Susceptible-Infected-Recovered) dynamics. This paper provides a novel proof of this principle for the existing SIR framework, showing that the total number of deaths or infections from an epidemic is decreasing in vaccination effort. Furthermore, it presents a novel model for vaccination which assumes that vaccines assigned to a subgroup are distributed randomly to the unvaccinated population of that subgroup. It suggests, using COVID-19 data, that this more accurately captures vaccination dynamics than the model commonly found in the literature. However, as the novel model provides a strictly larger set of possible vaccination policies, the results presented in this paper hold for both models.
Evaluation of a clinical decision support system for detection of patients at risk after kidney transplantation
Authors: Roller Roland , Mayrdorfer Manuel , Duettmann Wiebke , Naik Marcel G. , Schmidt Danilo , Halleck Fabian , Hummel Patrik , Burchardt Aljoscha , Möller Sebastian , Dabrock Peter , Osmanodja Bilgin , Budde Klemens 
Published: May 2022

AbstractPatient care after kidney transplantation requires integration of complex information to make informed decisions on risk constellations. Many machine learning models have been developed for detecting patient outcomes in the past years. However, performance metrics alone do not determine practical utility. Often, the actual performance of medical professionals on the given task is not known. We present a newly developed clinical decision support system (CDSS) for detection of patients at risk for rejection and death-censored graft failure. The CDSS is based on clinical routine data including 1516 kidney transplant recipients and more than 100 000 data points. Additionally, we conduct a reader study to compare the performance of the system to estimations of physicians at a nephrology department with and without the CDSS. Internal validation shows AUC-ROC scores of 0.83 for rejection, and 0.95 for graft failure. The reader study shows that although the predictions by physicians converge towards the suggestions made by the CDSS, performance in terms of AUC-ROC does not improve (0.6413 vs. 0.6314 for rejection; 0.8072 vs. 0.7778 for graft failure). Finally, the study shows that the CDSS detects partially different patients at risk compared to physicians without CDSS. This indicates that the combination of both, medical professionals and a CDSS might help detect more patients at risk for graft failure. However, the question of how to integrate such a system efficiently into clinical practice remains open.