Validation Panel Research Articles

Application of Gene Expression Microarray for the Classification of Ph-Like B-Cell Acute Lymphoblastic Leukemia.

Ph-like ALL has gene expression profile similar to Ph-positive ALL but without the BCR::ABL1 fusion. The disease presents higher rates of severe clinical features and is associated with unfavorable outcomes. There is still no standard pipeline for molecular characterization of the disease, and no valid predictor gene panel is available worldwide. We performed expression microarray on 25 B-cell ALL and 6 Ph-positive B-cell ALL to cluster and identify the transcriptional signature of Ph-like ALL. qRT-PCR was used to confirm the expression of candidate genes. Four out of 25 samples (16%) shared gene expression signatures related to and clustered with control Ph-positive samples. Analysis of genes differentially expressed in Ph-like B-cell ALL and evidentially functional in normal blood cell development and leukemogenesis, we selected genes as potential biomarkers for Ph-like B-cell ALL in our dataset: ADGRE2, CD9, EPHA7, FAM129C, TCL1A, and VPREB1. Those genes were filtered by Ph-like gene signatures obtained from distinct reliable data, resulting in five genes, CA6, CHN2, JAK1, JCHAIN, and PON2, selected for validation by qRT-PCR. The Ct values of genes, including CA6 (p = 0.0017), PON2 (p = 0.0210), TCL1A (p = 0.0064), and VPREB1 (p = 0.0338), were significant in Ph-like ALL. GSEA analysis identified VPREB1 as enrichment in the KRAS signaling pathway, and several genes that interact with VPREB1 were reported as critical molecules involved in the leukemogenesis of B-cell ALL. In summary, we demonstrate using a gene expression microarray for classifying Ph-like B-cell ALL and highlight VPREB1 as a potential biomarker for this disease.

OPTIMA-ID: development and validation of a medicine optimization tool for older adults with intellectual disability

ABSTRACT Background Older people (i.e. ≥40 years) with intellectual disability have unique medication needs and may experience high levels of potentially inappropriate prescribing. Despite the availability of tools to optimize older adults’ prescriptions, there is no comprehensive tool specifically for use in older adults with intellectual disability. We aimed to develop a tool for this purpose: Optimizing Pharmaco-Therapy and Improving Medication for Ageing with Intellectual Disability (OPTIMA-ID). Research design and methods A draft tool was developed based on literature review and clinical expertise. Focus groups with healthcare professionals and people with intellectual disability were conducted to refine the tool. The tool was presented electronically to an expert panel for Delphi validation. Median level of agreement and 75th percentile values were used to establish if consensus was reached. Criteria were accepted, rejected, revised or removed to develop the final tool. Results Following two Delphi rounds, consensus on the content of OPTIMA-ID was reached for 67 prescribing criteria, 63 of which were agreed upon after Round 1 and a further 4 criteria accepted after Round 2. Conclusions OPTIMA-ID contains 67 criteria that can optimize medications for older people with intellectual disability. Its effectiveness, feasibility and impact on patient outcomes need to be established.

Healthcare professionals perceptions of obesity management: An IMI2 SOPHIA qualitative study.

Understanding healthcare professionals' perceptions and approaches to obesity management is limited, as are the barriers impeding effective care. A questionnaire was developed to explore the perception, and barriers to obesity management. To ensure content validity, an expert and stakeholder panel evaluated the relevance and comprehension of each item. Consequently, a cross-sectional survey was administered to endocrinologists (Endo), general practitioners (GP), and pharmacists (Pharm). A 46-item questionnaire was developed, validated, and completed by 502 healthcare professionals (Endo: n = 127; GP: n = 138; Pharm: n = 237). The majority agreed that obesity is a chronic disease (Endo = 96%; GP = 92.7%; Pharm = 87%). The conversation about obesity management is mostly initiated by the healthcare professional (Endo = 95.3%; GP = 73.9%; Pharm = 5.9%) instead of the patient (Endo = 55.1%; GP = 21.7%; Pharm = 11.8%). All professionals stated unanimously that there is a need to optimise obesity care in Belgium with identified barriers: motivational (Endo = 90.8%; GP = 90.8%; Pharm = 89.2%), financial (Endo = 96.9%; GP = 88.5%; Pharm = 76.3%), and a lack of structure (Endo = 81.5%; GP = 78.6%; Pharm = 81.5%). A total of 42.4% of the healthcare providers indicated that they did not follow any additional training. These findings highlight that healthcare professionals recognise obesity as a chronic disease, but that barriers need to be addressed to enhance effective care and support for people living with obesity.

Development of a questionnaire for patient perception to functional appliances

ObjectiveTo developed and evaluate the validity, reliability, and Arabic translation of a questionnaire for preadolescent perception to removable functional appliances.Subjects and methodsA new questionnaire was drafted based on previously used questionnaires. Twelve orthodontic experts were selected within content and face validity panel and twenty preadolescents wearing functional appliances were participated in the face validation of the questionnaire. Two rounds of content validity were performed with the same experts. The final form of the validated questionnaire was translated from English to Arabic language. The content validity index (CVI) was used for content validity and the Cronbach’s alpha test was used to assess the internal consistency reliability of the questionnaire.ResultsDuring the first round of content validity, 50 items were relevant to the underlying construct (Item-CVI ≥ 0.78), while four items were considered not valid (Item-CVI < 0.78) and the average scale-CVI was 0.93. In terms of face validation by experts, the percentage of agreement was adequate (96.4%). The questionnaire was modified by removing the non-valid items, adding/modifying items, and merging some categories. For second round of content validity, all items were found to be valid (I-CVI ≥ 0.78) and the overall questionnaire had adequate content validity (Scale-CVI/Ave = 0.94). The translated valid questionnaire also achieved a perfect agreement (100%) for face validity by patients. The internal consistency was appropriate (≥ 0.7).ConclusionsA new valid, reliable, and translated questionnaire (English and Arabic versions) that cover the majority of aspects of patients’ perception during treatment with removable functional appliances has been developed.

High-throughput diagnostic markers for foliar fungal disease resistance and high oleic acid content in groundnut

BackgroundFoliar diseases namely late leaf spot (LLS) and leaf rust (LR) reduce yield and deteriorate fodder quality in groundnut. Also the high oleic acid content has emerged as one of the most important traits for industries and consumers due to its increased shelf life and health benefits.ResultsGenetic mapping combined with pooled sequencing approaches identified candidate resistance genes (LLSR1 and LLSR2 for LLS and LR1 for LR) for both foliar fungal diseases. The LLS-A02 locus housed LLSR1 gene for LLS resistance, while, LLS-A03 housed LLSR2 and LR1 genes for LLS and LR resistance, respectively. A total of 49 KASPs markers were developed from the genomic regions of important disease resistance genes, such as NBS-LRR, purple acid phosphatase, pentatricopeptide repeat-containing protein, and serine/threonine-protein phosphatase. Among the 49 KASP markers, 41 KASPs were validated successfully on a validation panel of contrasting germplasm and breeding lines. Of the 41 validated KASPs, 39 KASPs were designed for rust and LLS resistance, while two KASPs were developed using fatty acid desaturase (FAD) genes to control high oleic acid levels. These validated KASP markers have been extensively used by various groundnut breeding programs across the world which led to development of thousands of advanced breeding lines and few of them also released for commercial cultivation.ConclusionIn this study, high-throughput and cost-effective KASP assays were developed, validated and successfully deployed to improve the resistance against foliar fungal diseases and oleic acid in groundnut. So far deployment of allele-specific and KASP diagnostic markers facilitated development and release of two rust- and LLS-resistant varieties and five high-oleic acid groundnut varieties in India. These validated markers provide opportunities for routine deployment in groundnut breeding programs.

A genome-wide association study for resistance to Fusarium wilt (Fusarium oxysporum f. sp. vasinfectum) race 4 in diploid cotton (Gossypium arboreum)and resistance transfer to tetraploid Gossypium hirsutum.

Fusarium wilt, caused by the soilborne fungus Fusarium oxysporum f. sp. vasinfectum (FOV), is a devastating disease affecting cotton (Gossypium spp.) worldwide. Understanding the genetic basis of resistance in diploid cotton and successfully transferring the resistance to tetraploid Upland cotton (G. hirsutum) are crucial for developing resistant cotton cultivars. Although numerous studies have been conducted to investigate the genetic basis of Fusarium wilt in tetraploid cotton, little research has been conducted on diploid species. In this study, an association mapping panel consisting of 246 accessions of G. arboreum, was used to identify chromosomal regions for FOV race 4 (FOV4) resistance based on foliar disease severity ratings in four greenhouse tests. Through a genome-wide association study (GWAS) based on 7,009 single nucleotide polymorphic (SNP) markers, 24 FOV4 resistance QTLs, including three major QTLs on chromosomes A04, A06, and A11, were detected. A validation panel consisting of 97 diploid cotton accessions was employed, confirming the presence of several QTLs. Evaluation of an introgressed BC2F7 population derived from G. hirsutum/G. aridum/G. arboreum showed significant differences in disease incidence and mortality rate, as compared to susceptible and resistant controls, suggesting that the resistance in G. arboreum and/or G. aridum was transferred into Upland cotton for the first time. The identification of novel major resistance QTLs, along with the transfer of resistance from the diploid species, expands our understanding of the genomic regions involved in conferring resistance to FOV4 and contributes to the development of resilient Upland cotton cultivars.

Development of the ARDS-derived gene panel for lung adenocarcinoma prognosis stratification and experiment validation of CCL20 expression.

Acute respiratory distress syndrome (ARDS) is a life-threatening condition characterized by lung inflammation and high mortality rates. Lung cancer, specifically lung adenocarcinoma (LUAD), is a major cause of cancer-related deaths worldwide. Patients with LUAD, particularly those undergoing chemotherapy, are more likely to develop ARDS. ARDS inflicts major malfunctioning in the immune system. We suspected a certain shared pathogenic mechanism between these diseases. This study analyzed 503 LUAD patients from the TCGA-LUAD cohort as the training set, 85 LUAD cases from the GSE30219 cohort as the validation set, and 24 RNA-seq samples from ARDS mice model and control groups in the GSE2411 cohort. The differentially expressed genes (DEGs) of ARDS were analyzed using the limma package and screened by Cox and Lasso analysis. ssGSEA and xCell algorithms were utilized for immune landscaping. RT-qPCR analysis was used to determine the mRNA levels of key genes in both the LPS-induced ARDS model and human LUAD cell lines. We identified DEGs between ARDS and control groups, which were highly associated with cytokine production and leukocyte migration. A prognosis model for LUAD patients was developed based on the expressions of the key genes in the ARDS-derived DEGs, including FMO3, IL1R2, CCL20, CFTR, and GADD45G. A satisfactory efficacy was observed in both the training and validation cohorts. The model demonstrated increased effectiveness in predicting the intratumor immune profile and mutation status of LUAD. Moreover, we utilized LPS to induce the ARDS model, which resulted in elevated expressions of IL1R2 and CCL20. Additionally, CCL20 was upregulated in cancerous LUAD cell lines. We developed an ARDS-based model for stratifying LUAD prognosis. CCL20 was found to be elevated in both the ARDS model and LUAD, suggesting a shared underlying mechanism of these two diseases.

The Effects of Genetic Distance and Genetic Diversity on Genomic Prediction Accuracy for Soybean Quantitative Disease Resistance to Phytophthora sojae

Assessing quantitative disease resistance and other complex traits can be time- and space-consuming, limiting the number of lines that can be evaluated in a breeding program. A potential improvement is the application of genomic prediction models, where genotypic data are used to calculate genomic estimated breeding values, referred to as genomic selection. Genomic prediction uses training datasets, where a germplasm panel is phenotyped and genotyped to calculate genomic estimated breeding values in a validation panel of lines based solely on genotypic data. To develop an initial phenotypic dataset, breeders may consider utilizing previously phenotyped lines in a publicly available dataset, such as plant introductions (PIs) from the USDA Soybean collection. A relevant question is, how effective is genomic prediction across diverse training and prediction panels? To answer this, we used previously collected phenotypic data for quantitative disease resistance toward Phytophthora sojae. Diverse germplasm panels were represented by sets of PIs originating from the United States, the Republic of Korea, and worldwide, for a total collection of 1,768 PIs. The accuracy of the prediction model was significantly influenced by population differentiation between panels, as well as genetic and phenotypic diversity. Low prediction accuracy resulted when the panel used to create the prediction model was highly differentiated from the validation panel. However, the addition of a small number of accessions to the training panel that were more closely related to the validation panel resulted in increased accuracy. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

The diffusion of racial validation panels in public universities - institutions and organizational change

Resumo Esse artigo mobiliza a literatura sobre isomorfismo institucional e movimentos sociais para explicar a difusão no Brasil de procedimentos de validação das autodeclarações dos candidatos à admissão em universidades federais por meio de cotas raciais. A difusão desses procedimentos transformou o modo como o direito às ações afirmativas é compreendido e produziu mudanças organizacionais. Por meio da análise de documentos e entrevistas, o artigo identifica os mecanismos coercivos, miméticos e normativos em jogo e examina sua gênese. Ele mostra que esses derivaram das interações entre estudantes universitários, funcionários técnico-administrativos e docentes das universidades, assim como organizações do movimento negro e de agências do estado, engajados no objetivo de proteger as ações afirmativas. Implicações para estudar mudança no ensino superior e nas relações raciais no Brasil são discutidas.

Allplex HPV HR Detection assay fulfils all clinical performance and reproducibility validation requirements for primary cervical cancer screening

Human papillomavirus (HPV)-based screening offers better protection against cervical cancer compared to cytology, but HPV screening assays must adhere to validation requirements of the international guidelines to ensure optimal performance. Allplex HPV HR Detection (Allplex) assay, launched in the late 2022, is a fully automated real-time PCR-based assay utilizing innovative technology that enables quantification and concurrent distinction of 14 high-risk HPV genotypes (HPV16,18,31,33,35,39,45,51,52,56,58,59,66 and 68). We assessed the validity of the Allplex for cervical cancer screening purposes, via comparison to a clinically validated comparator assay (Hybrid Capture 2; HC2), and through assessment of intra-laboratory reproducibility and inter-laboratory agreement. A clinical validation panel comprised of 973 residual ThinPrep samples was obtained from women aged 30-64 years participating in the organized Slovenian screening program, of these 863 were from women undergoing their regular screening visit after a previous negative screen test while 110 were from women with underlying cervical intraepithelial neoplasia grade 2 or worse (CIN2+) lesions. The Allplex's relative clinical sensitivity for detection of CIN2+ and CIN3+ were 1.01 (95%CI;0.98-1.04) and 0.98 (95%CI;0.95-1.02), compared to that of HC2. At recommended thresholds of ≥98% and ≥90%, the Allplex's clinical sensitivity and specificity (p=0.0004 and p=0.02, respectively) were non-inferior to HC2. High intra-laboratory reproducibility and inter-laboratory agreement, both overall (98.1% and 97.9%, respectively) and at genotype level (>98.7%) was observed. In addition, analytical genotype-specific performance of Allplex was compared to that of its predecessor Anyplex HPV HR; high overall agreement was observed (96.3%; kappa value 0.88), with some variations in performance. In conclusion, Allplex met all validation criteria described in the international guidelines on sensitivity, specificity and laboratory reproducibility and can be considered clinically validated for primary cervical cancer screening.

Durum wheat heat tolerance loci defined via a north-south gradient.

The global production of durum wheat (Triticum durum Desf.) is hindered by a constant rise in the frequency of severe heat stress events. To identify heat-tolerant germplasm, three different germplasm panels ("discovery," "investigation," and "validation") were studied under a range of heat-stressed conditions. Grain yield (GY) and its components were recorded at each site and a heat stress susceptibility index was calculated, confirming that each 1°C temperature rise corresponds to a GY reduction in durum wheat of 4.6%-6.3%. A total of 2552 polymorphic single nucleotide polymorphisms (SNPs) defined the diversity of the first panel, while 5642 SNPs were polymorphic in the "investigation panel." The use of genome-wide association studies revealed that 36 quantitative trait loci were associated with the target traits in the discovery panel, of which five were confirmed in a "subset" tested imposing heat stress by plastic tunnels, and in the investigation panel. A study of allelic combinations confirmed that Q.icd.Heat.003-1A, Q.icd.Heat.007-1B, and Q.icd.Heat.016-3B are additive in nature and the positive alleles at all three loci resulted in a 16% higher GY under heat stress. The underlying SNPs were converted into kompetitive allele specific PCR markers and tested on the validation panel, confirming that each explained up to 9% of the phenotypic variation for GY under heat stress. These markers can now be used for breeding to improve resilience to climate change and increase productivity in heat-stressed areas.

Improving gene expression prediction models through the use of meta‐analysis summary statistics

AbstractBackgroundBy focusing on a gene‐level rather than a single‐variant basis, transcriptome‐wide association studies (TWAS) assess the role of genetically regulated gene expression in disease risk and improve statistical power by reducing the multiple testing burden by over a 100‐fold. A key limitation of current TWAS approaches is the requirement for dense individual‐level datasets with both genotypes and gene expression measures to produce effective expression prediction models. We sought to improve the statistical power of AD TWAS by leveraging easily accessible summary statistics taken from large‐scale expression quantitative trait loci (eQTL) meta‐analyses.MethodWe used eQTLGen Whole Blood cis‐eQTL data (N = 31,684) as our source of meta‐analysis summary statistics. To perform gene‐based elastic‐net regressions using the summary statistics, we used the lassosum R package (Mak et al. 2017) with 1000 Genomes data as a genomic reference and GTEx v8 genotype, normalized Whole Blood gene expression and covariate data (N = 670) as a testing panel for model validation and dynamic selection of the optimal mixing/penalty parameters. The SNP‐weights generated by our models were subsequently applied to AD meta‐analysis summary statistics from Kunkle et al. 2019 (AD Cases = 21,982; Controls = 44,944) and Bellenguez et al. 2022 (AD/ ‘proxy’ AD Cases = 111,326; Controls = 677,663) via S‐PrediXcan to assess whether predicted gene expression is associated with AD risk.ResultWe found on average a 3.3% (SD: 0.05%) significant improvement in the predictive performance for 93.3% of genes models (N = 2,787) when using the same SNPs as the PredictDB model. Using models with the restricted SNP set, we identified four genome‐wide significant gene expression models (CTDNEP, p = 3.2e‐9; STK4, p = 1.6e‐13; RPS14, p = 8.8e‐38; POLR1H, p = 5.6e‐45) using Kunkle et al. 2019 summary statistics relative to only one using the PredictDB model (FBXO46, p = 6.6e‐15). When applying the Bellenguez et al. 2022 summary statistics, which contains a broader AD phenotype thru the inclusion of ‘proxy’ cases, we identified 12 genome‐wide significant gene expression models (Range: CHRNA2, p = 2.6e‐8; SLC24A4, p = 4.5e‐16) associated with AD.ConclusionOur findings show AD association studies based on TWAS approaches may be improved by meta‐analysis reference panels.

Genomic regions of durum wheat involved in water productivity.

Durum wheat is a staple food in the Mediterranean Basin, mostly cultivated under rainfed conditions. As such, the crop is often exposed to moisture stress. Therefore, the identification of genetic factors controlling the capacity of genotypes to convert moisture into grain yield (i.e., water productivity) is quintessential to stabilize production despite climatic variations. A global panel of 384 accessions was tested across 18 Mediterranean environments (in Morocco, Lebanon, and Jordan) representing a vast range of moisture levels. The accessions were assigned to water responsiveness classes, with genotypes 'Responsive to Low Moisture' reaching an average +1.5 kg ha-1 mm-1 yield advantage. Genome wide association studies revealed that six loci explained most of this variation. A second validation panel tested under moisture stress confirmed that carrying the positive allele at three loci on chromosomes 1B, 2A, and 7B generated an average water productivity gain of +2.2 kg ha-1 mm-1. These three loci were tagged by kompetitive allele specific PCR (KASP) markers, and these were used to screen a third independent validation panel composed of elites tested across moisture stressed sites. The three KASP combined predicted up to 10% of the variation for grain yield at 60% accuracy. These loci are now ready for molecular pyramiding and transfer across cultivars to improve the moisture conversion of durum wheat.

White spot lesions in orthodontics: consensus statements for prevention and management.

To establish consensus recommendations for clinicians to manage white spot lesions (WSLs) during orthodontic treatment. Three task force members reviewed the literature to identify best practices for minimizing WSLs during orthodontic treatment. Each draft statement was read to the task force members by a facilitator, followed by voting, accepting, or editing if necessary. The statements were then sent electronically by an independent third party (Magellan Medical Technology Consultants Inc, Minneapolis, Minn) to a previously formed content validation panel consisting of 20 independent private practitioners and clinical academicians for validation. Twenty-one statements were developed and sent for content validation. While 19 statements achieved a content validation index (CVI) of 0.78, two items did not. These items were edited by the task force members based on qualitative feedback from content validation participants. Each of these revised statements did achieve a CVI of 0.78 on second evaluation from the content validation panelists and therefore were included in this document. To reduce the risk of WSLs, it is essential to implement individualized caries management measures based on a comprehensive assessment of the patient's oral and systemic health. Effective at-home and professional mechanical and chemical plaque control should be implemented for high-risk orthodontic patients. Fluoride to support prevention and materials such as orthodontic sealants should also be used to provide a physical barrier around the brackets in high-risk patients. By following these guidelines, orthodontic professionals can help promote oral health and minimize the need for restorative treatment.

KEAP1/NFE2L2 Pathway Signature Outperforms KEAP1/NFE2L2 Mutation Status and Reveals Alternative Pathway-Activating Mutations in NSCLC

IntroductionActivation of the antioxidant KEAP1/NFE2L2 (NRF2) pathway leads to increased glutamine dependence and an aggressive phenotype in NSCLC. Because this pathway has been explored as a clinical target, we developed a transcriptomic signature for identifying KEAP1/NFE2L2-activated tumors. MethodsA total of 971 NSCLC samples were used to train an expression signature (K1N2-score) to predict KEAP1/NFE2L2 mutations. There were 348 in-house NSCLCs that were analyzed using a NanoString expression panel for validation. ResultsThe 46-gene K1N2 score robustly predicted KEAP1/NFE2L2 mutations in the validation set irrespective of histology and mutation (area under the curve: 89.5, sensitivity: 90.2%), suggesting that approximately 90% of KEAP1/NFE2L2 mutations are pathway-activating. The K1N2-score outperformed KEAP1/NFE2L2 mutational status when predicting patient survival (score p = 0.047; mutation p = 0.215). In K1N2 score–positive but KEAP1/NFE2L2 wild-type samples, enrichment testing identified SMARCA4/BRG1 and CUL3 mutations as mimics of KEAP1/NFE2L2 mutations. ConclusionsThe K1N2-score identified KEAP1/NFE2L2-activated NSCLC by robustly detecting KEAP1/NFE2L2mut cases and discovering alternative genomic activators. It is a potential means for selecting patients with a constitutively active KEAP1/NFE2L2 pathway.

Co-expression network analysis of diverse wheat landraces reveals markersof early thermotolerance and a candidate master regulator of thermotolerance genes.

Triticum aestivum L. (bread wheat) is a crop relied upon by billions of people around the world, as a major source of both income and calories. Rising global temperatures, however, pose a genuine threat to the livelihood of these people, as wheat growth and yields are extremely vulnerable to damage by heat stress. Here we present the YoGI wheat landrace panel, comprising 342 accessions that show remarkable phenotypic and genetic diversity thanks to their adaptation to different climates. We quantified the abundance of110 790 transcripts from the panel and used these data to conduct weighted co-expression network analysis and to identify hub genes in modules associated with abiotic stress tolerance. We found that the expression of three hub genes, all heat-shock proteins (HSPs), were significantly correlated with early thermotolerance in a validation panel of landraces. These hub genes belong to the same module, with one (TraesCS4D01G207500.1) being a candidate master-regulator potentially controlling the expression of the other two hub genes, as well as a suite of other HSPs and heat-stress transcription factors (HSFs). In this work, therefore, we identify three validated hub genes, the expression of which can serve as markers of thermotolerance during early development, and suggest that TraesCS4D01G207500.1 is a potential master regulator of HSP and HSF expression - presenting the YoGI landrace panel as an invaluable tool for breeders wishing to determine and introduce novel alleles into modern varieties, for the production of climate-resilient crops.

Abstract LB054: Establishment of an infrastructure for rapid pandemic response at the Frederick National Laboratory

Abstract The sudden onset of the 2019 SARS-CoV-2 pandemic required agile development of standards and efficient validation of assays to assess prevalence of infection as well as immune responses to infection and vaccination. Leveraging their experience in HPV serology and standards, the Vaccine, Immunity and Cancer Directorate (VICD) at the Frederick National Laboratory for Cancer Research (FNCLR) pivoted to address this unmet need in SARS-Co-V2 serology clinical testing and research. This standardization effort required the collection and processing of large volumes of blood from SARS-Co-V2 infected and uninfected individuals into serum and peripheral blood mononuclear cells (PBMCs). Collaborations with specimen collection sites across the United States were established. Following qualification for anti-SARS-CoV-2 IgG and IgM levels in independent laboratories, VICD assembled reference evaluation panels, which were used to assist the FDA’s performance evaluation of commercial assays submitted for EUA approval. To date, 185 different shipments of the standard or validation panel have been sent to both domestic and international labs. These materials are also available to the SARS-CoV-2 serology community for assay calibration and performance evaluation which greatly facilitates assay data harmonization. In addition, the NCI Serological Sciences Network (SeroNet) was born from this initiative and expertise, resulting in the establishment of Capacity Building Centers (CBCs) for sample collection from different healthy, cancer and immunocompromised cohorts at Mount Sinai, Arizona State University, the University of Minnesota, and Northwell Feinstein. The NCI and FNLCR simultaneously collaborated to develop a network of investigators focused on advancing research on the immune response to SARS-CoV-2 infection and vaccination among diverse and vulnerable populations, including cancer patients. Their research has resulted in over 326 peer-reviewed publications. The CBC’s have enrolled patients in longitudinal studies, resulting in a centralized collection of annotated, well characterized serum, PBMCs and clinical data. Numerous cancer cohorts, but predominantly Multiple Myeloma, are included. Furthermore, technology development was supported at the CBC’s. Based upon this success, the VICD in collaboration with NCI is pursuing an even more innovative effort in pandemic preparedness to establish a Center for Serology and Data Emergency Preparedness (CESDEP); a global network able to activate and pivot to address pandemic-level threats, while continuing to expand the development of immunological assays that can inform clinical decisions for cancer and other immunocompromised patients. Citation Format: Nancy V. Roche, Troy Kemp, Ligia Pinto, Tom Hickey. Establishment of an infrastructure for rapid pandemic response at the Frederick National Laboratory [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB054.

Leveraging the use of meta‐analysis summary statistics to improve gene expression prediction models

AbstractBackgroundGenetically regulated gene expression as assessed via Transcriptome‐wide association studies (TWAS) can be used to elucidate the mechanistic basis Alzheimer’s Disease. A limitation of current TWAS approaches is the requirement for individual‐level datasets with both genotypes and gene expression measures to produce effective prediction models. We sought to improve the predictive performance of existing gene‐based models by leveraging easily accessible summary statistics that are powered by large sample sizes.MethodsBrain cis‐eQTL data produced from a large‐scale meta‐analysis was restricted to data from European‐descent individuals and samples taken from Brain‐Cortex (Average_N=2,547). The effect size estimates, and their standard errors from the individual cohorts (N=14) were used to re‐run a meta‐analysis excluding GTEx data via METAL.To perform gene‐based elastic‐net regressions using the produced summary statistics, the lassosum R package produced by Mak et al. 2017 was applied to genotype data from the 1,000 Genomes data (GRCh38) serving as a reference panel and GTEx_v8 genotype, normalized Brain‐Cortex gene expression, and covariate data (N=205) serving as a testing panel for model validation and dynamic selection of the optimal mixing/penalty parameters. The maximum R2 produced by this pipeline was compared to elastic‐net models generated by PredictDB using Brain‐Cortex GTEx_v8 data where the mixing parameter was set at 0.5.ResultsOur pipeline produced gene‐based models that had an improved predictive performance averaging 9.8% (SD: 7%) based on R2 over PredictDB models in 93.7% of genes tested (N=3,965) when restricting our pipeline to SNPs found in PredictDB. The optimal mixing parameter dramatically differed from PredictDB with a median of 0.009 highlighting the utility of including variants with small effects. Even restricting the mixing parameter to 0.5 for genes with a converged model, our pipeline outperformed PredictDB in 85% of genes (N=369). By examining expression prediction metrics to genes from the KEGG Alzheimer’s Disease pathway (hsa05010), our pipeline had improved performance in 100% of matched genes (N=30).ConclusionWe demonstrate improvement upon existing TWAS reference panels and increase gene‐expression predictive performance by leveraging the power of summary statistics. Our findings show AD association studies based on TWAS approaches may be improved by meta‐analysis reference panels.

P500 Validation panel for MALDI-TOF identification of fungi

Poster session 3, September 23, 2022, 12:30 PM - 1:30 PMSciensano, the Belgian federal scientific institute for public and animal health, houses the BCCM/IHEM Fungi Collection which contains more than 15 000 strains, belonging to over 1 500 different species. The collection is managed according to ISO 9001 standards.Its purpose is to make fungal strains available for academics, clinicians, industry, and education.Fungal pathogens are not as often encountered as bacteria in the clinical laboratory. Additionally, laboratories may not have the knowledge or logistics for the long-term preservation of axenic fungal isolates. Without an array of fungal strains with confirmed identity, it is complicated to implement new protocols and equipment when these need to be validated for the identification of fungi.To short-cut this problem and support laboratories in identifying clinical fungi in routine activities, BCCM/IHEM has developed two validation panels for the identification of fungi via MALDI-TOF mass spectrometry: there is a validation panel with yeasts and a validation panel with filamentous fungi. The selection of strains is based on species that are routinely encountered in a clinical laboratory, and also contains some rarer, but emerging fungal pathogens, like Trichophyton indotineae and Candida auris. The identity and purity of the strains in these panels have been verified according to ISO 17025 accredited protocols. This allows the laboratory to evaluate in a short term the extraction protocol, the MALDI-TOF machine, and the database of reference mass spectra.

A novel rRNA hybridization-based approach to rapid, accurate Candida identification directly from blood culture.

Candida bloodstream infections cause considerable morbidity and mortality, yet slow diagnostics delay recognition, worsening patient outcomes. We develop and validate a novel molecular approach to accurately identify Candida species directly from blood culture one day faster than standard workflows.