Academic literature on the topic 'Variant effect prediction methods development and assessment'

Abstract Interpretation of genomic variation plays an essential role in the analysis of cancer and monogenic disease, with applications ranging from basic research to clinical decisions. Yet the field lacks a clear consensus on the appropriate level of confidence to place in variant impact and interpretation methods, for both well-established oncogenes as well as less understood genes. The Critical Assessment of Genome Interpretation (CAGI, \'kā-jē\) is a community experiment to objectively assess computational methods for predicting the phenotypic impacts of genomic variation. CAGI participants are provided genetic variants and make blind predictions of resulting phenotype. Independent assessors evaluate the predictions by comparing them against experimental and clinical data. Six CAGI editions involving over 60 experiments have taken place to date. Results have been described in two special issues of Human Mutation (vol. 38(9) and vol. 40(9)). About a quarter of CAGI experiments have involved genes implicated in cancer, including variants in BRCA1, BRCA2, CHEK2, the MRN complex (RAD50, MRE11, and NBS1), FXN, NSMCE2 (coding for SUMO ligase), NPM-ALK CDKN2A, PTEN, TPMT, STK11, p16 and TP53. In the ENIGMA consortium challenge, a total of 326 germline BRCA1/BRCA2 missense and in-frame indel variants were provided. The most successful predictions achieved a ROC AUC of 0.94 and were derived from a metapredictor that explicitly considered the population frequency of each variant, trained on cancer data, and included the role of altered splicing. In challenges exploring the role of protein stability in cancer progression, biophysical and structure-based methods are among the top performers and have provided insights into underlying molecular mechanisms. This was the case for the p16 challenge involving variants of unknown significance in familial malignant melanoma, the PTEN and TPMT challenges that measured variant effect on protein stability via intracellular abundance in a high-throughput assay, and the p53 rescue challenge in which predictors managed to successfully identify a handful of double mutants, among a set of 14,668 total variants, that reactivated the damaged protein. Cancer challenges involving breast cancer pharmacogenomics, case-controls, splicing and polygenic risk scores (PRS) have been moderately successful but show promise for the future. A key finding from CAGI is that for most missense challenges, including cancer, it is possible to relate phenotype values to a pathogenicity threshold, and so deduce potential performance in a clinical setting. The results suggest that computational methods are generally more reliable than recognized in the current clinical use guidelines, warranting a reevaluation of their role in clinical variant interpretation. Results from the ENIGMA and other BRCA challenges support this observation but more data are needed. Overall, CAGI has helped establishing the state of art in genome interpretation, encouraged new methodological developments, and informed the clinical application of computational predictors. Detailed information about CAGI may be found at https://genomeinterpretation.org. Citation Format: Constantina Bakolitsa, Shantanu Jain, Gaia Andreoletti, Roger A. Hoskins, Predrag Radivojac, John Moult, Steven E. Brenner, CAGI Participants. The Critical Assessment of Genome Interpretation: A community experiment that informs use of methods for germline cancer variant impact prediction [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB152.

Introduction: Congenital heart disease (CHD) is the most common congenital abnormality and the main cause of infant mortality worldwide. Some of the mutations that occur in the GATA4 gene region may result in different types of CHD. Here, we report our in silico analysis of gene variants to determine the effects of the GATA4 gene on the development of CHD. Methods: Online 1000 Genomes Project, ExAC, gnomAD, GO-ESP, TOPMed, Iranome, GME, ClinVar, and HGMD databases were drawn upon to collect information on all the reported GATA4 variations.The functional importance of the genetic variants was assessed by using SIFT, MutationTaster, CADD,PolyPhen-2, PROVEAN, and GERP prediction tools. Thereafter, network analysis of the GATA4protein via STRING, normal/mutant protein structure prediction via HOPE and I-TASSER, and phylogenetic assessment of the GATA4 sequence alignment via ClustalW were performed. Results: The most frequent variant was c.874T>C (45.58%), which was reported in Germany.Ventricular septal defect was the most frequent type of CHD. Out of all the reported variants of GATA4,38 variants were pathogenic. A high level of pathogenicity was shown for p.Gly221Arg (CADD score=31), which was further analyzed. Conclusion: The GATA4 gene plays a significant role in CHD; we, therefore, suggest that it be accorded priority in CHD genetic screening.

Since sheet-bulk metal forming processes inherit properties of both sheet and bulk metal forming processes, their analysis requires on one side following certain methods conventionally devised in these process classes analyses whereas on the other side leaving certain customs out. For instance, inherent anisotropy of the rolled sheet has to be taken into account whereas due to non-vanishing out of plane stress component, analysis with thin shells using the plane stress state assumption is no more applicable. Similarly, methods based on necking instabilities, i.e. forming limit diagrams, which are typically used in sheet metal formability assessment; fall short in sheet-bulk metal formability prediction. In the present study, we propose a local approach to fracture, more specifically a phenomenologically based Lemaitre variant CDM model, devised frequently in bulk metal forming analysis, as an alternative. For this purpose, a combined nonlinear isotropic-kinematic hardening plasticity with Hill48 type initial anisotropy is fully coupled with isotropic damage. Together with the concept of effective stress and equivalent strain principle, quasi-unilateral damage evolution is used, where the energetic contribution of the compressive stress state to the damage driving force is scaled with a so-called crack closure parameter, . For the quasi unilateral damage evolution is inactive whereas for it is fully active which completely suppresses the development of damage under compressive stress states. The framework devises state coupling between elasticity and damage and kinematic coupling between plasticity and damage which increases the relative effect of on the eventual damage development. To this end, a direct extension to the finite strains for metal forming analysis is realized using a corotational formulation and the developed framework is implemented as a VUMAT subroutine for ABAQUS Explicit. For evaluation of the predictive capability of the model, teeth forming process results for DC04 reported in Soyarslan et al. 2011, An Experimental and Numerical Assessment of Sheet-Bulk Formability of Mild Steel DC04, Journal of Manufacturing Science and Engineering, Vol. 133 6, (2011) S. (061008) 1-9, are used. Mechanical material characterization studies are realized using a hybrid experimental-numerical procedure. This methodology relies on minimizing the difference between the experimentally handled global clamp force demand diagrams and the diagrams from the simulations at the complete range of the experiments involving fracture. As known finite element solutions with softening material models are prone to pathological mesh dependence. For this fact, a crack band method is used where the minimum element size, as a controlling parameter of the localization size, is also fitted through the characterization studies and identically used in the process simulations. The simulations show that a correct prediction of the zone and time of fracture is possible for the selected process whereas since the teeth formation process is mainly a compressive process, once the quasi-unilateral damage development is not used, i.e. for , a premature crack prediction is recorded which is not compatible with the experimental findings.

The Aim. This paper examines the problem of reliability of aptitude screening currently in place in commercial aviation in terms of its indiscriminate applicability to males and females. The task consisted in evaluating some professionally important qualities in males and females, who have successfully completed aptitude screening while being admitted to the aviation school, and identify the presence or absence of differences between the obtained results. For that purpose, a research was conducted that involved 60 third-year traffic controller students of the Saint Petersburg State University of Civil Aviation (35 males and 25 females).Methods. The psychodiagnostic method included the Prognoz-1 and Prognoz-2 stress tolerance evaluation forms developed in the S.M. Kirov Military Medical Academy, H.J. Eysenck intellectual development test, A. Buss and A. Durkee hostility assessment forms. The authors’ earlier findings were also used. Statistical processing was performed using correlation analysis and Pearson’s chi-squared test.Results. The analysis of psychodiagnostic findings has shown the absence of positive differences in the intellectual development of males and females in the observed group. In general, the intelligence of the study participants was sufficiently high (121.17 average IQ for males and 123.04 for females). The assessment of the stress tolerance of the surveyed group using two different variants of the Prognoz forms also has not identified any significant differences between males and females (stress tolerance of females is somewhat lower, than that of males, but the identified difference is obviously not crucial). However, both among males (1 person) and females (1 person) participants were identified, for whom the prediction per both diagnostic method was “unfavourable”. Positive differences between the examined males and females were identified in terms of tendency towards physical aggression (A. Buss and A. Durkee test).Conclusions. The psychodiagnostic method used as part of this work have not identified fundamental gender differences. An exception is the tendency towards physical aggression. In females this indicator is clearly lower, though there are girls who display high aggressiveness. Most experimental subjects demonstrated high stress tolerance and sufficiently high level of intellectual development. And while the examined group does not display clear differences in IQ (there are reasons to believe that the larger is the surveyed group the less significant are the positive differences between males and females in terms of intellectual development), however, the trend of female aviation specialists having overall higher IQ can be observed. The research must continue, extending the range of assessment methods, including alternative approaches that do not involve personality inventories, while simultaneously evaluating the extent of professionally important psychological qualities of aviation specialists, yet not with respect to gender, but in accordance with a candidate’s identified gender type.

Summary. Purpose: to develop prognostic criteria for the outcomes of ART programs in women with infertility in PCOS based on molecular genetic predictors of folliculogenesis disorders. Material and research methods. To solve the tasks set in the work, 125 women were examined: group first - 45 women with primary PCOS and infertility; group second - 46 women with infertility and PCOS in preparation for ART; group third 26 conditionally healthy women. Based on the foregoing, we presented the data of our own studies on the assessment of the state, the genes of steroid hormones (CYP17A1-rs743572, CYP19A1-rs247015) based on the analysis of laboratory data. Results and its discussion. Regarding the influence of the polymorphism of the CY19A1 rs2470152 gene on the development of PCOS, mutant alleles were found to be significantly higher in patients than in the control group. When we divided the main group into MC(+) and MC(-) in terms of CYP19A1 and compared with the control group, we found that the homozygous mutant genotype was found to be greater in the MC(+) and MC(-) group compared to the control group. With this, we can conclude that the homozygous mutational form of the CYP19A1 gene plays a convincing inducible role in PCOS and our result was significant (chi2 - 5.74; p<0.02 in the main group; chi2=5.2; p=0.02 in patients with metabolic syndrome and chi2=3.9; p<0.05 in patients without metabolic syndrome). However, the study did not reveal an induced effect on the heterozygous genotype in the development of PCOS (chi2<3.85; p>0.05). At the same time, the wild-type homozygous variant played a protective role in terms of the appearance of PCOS in the main group, as well as in the MC (+) and MC (-) groups (OR≥0.5). When it comes to the Hardy Weinberg equation, we found no significant difference between the expected and observed results in the main group. Estimates of polymorphism prediction efficiency, as already mentioned, showed only 0.6, which means that the prediction efficiency was not reliable in terms of mutant allele and genotype. In conclusion, from the study of CY17A1 polymorphism in patients with PCOS, it can be said that the GG mutant genotype was statistically significantly more common in patients compared to the control group. When dividing PCOS patients, they were divided into groups and compared with the control group, MS+ PCOS patients had a lower level of the mutant form (GG) genotype compared to the control group, but in MS-PCOS patients compared to the control group, the mutant gene was determined more.

Введение. Хроническая обструктивная болезнь легких (ХОБЛ) является мультифакторным заболеванием, в развитии которого определенная роль отводится полиморфизмам в структуре генов, кодирующих патогенетически значимые белковые молекулы.Цель. Изучение ассоциации полиморфизмов генов белков, участвующих в патогенезе заболевания, с риском развития ХОБЛ в белорусской популяции.Материалы и методы. Методом полимеразной цепной реакции проведено генотипирование полиморфных локусов генов rs4508917 (CXCL10), rs2280788 (CCL5), rs2228014 (CXCR4), rs333 (CCR5), rs1801275 (IL4R), rs2243250 (IL4), rs1800795 (IL6), rs1800896 (IL10), rs1800629 (TNF-α),rs2234693 (ESR1) и rs731236 (VDR) у 95 человек, страдающих ХОБЛ, и 95 здоровых добровольцев. Сравнительный анализ распределения частот генотипов между группами пациентов с ХОБЛ и здоровых лиц проведен с помощью программы SPSS на основании оценки критерия χ2 и точного критерия Фишера. Для определения вклада генотипов, ассоциированных с развитием ХОБЛ, в формировании предрасположенности к заболеванию рассчитаны показатели отношения шансов. Анализ межгенного взаимодействия выполнен с использованием программы MDR.Результаты. Установлено, что носительство гомозиготного генотипа, содержащего аллель А, полиморфного варианта rs1800896 (IL10) связано с повышенным риском формирования ХОБЛ. В отношении исследуемых групп определена ассоциация гетерозиготных генотипов полиморфизмов rs2280788 (CCL5) и rs2234693 (ESR1) с увеличением вероятности развития заболевания. Генотипы полиморфных локусов rs1800795 (IL6) и rs1801275 (IL4R), имеющие минорные аллели, связаны с пониженной восприимчивостью к ХОБЛ по доминантному типу наследования. Анализ межгенных взаимодействий выявил рисковые и протективные сочетания генотипов исследуемых генов в отношении возникновения ХОБЛ. Проведенное исследование установило значимость сочетанного влияния полиморфных локусов генов rs1800795 (IL6), rs1800896 (IL10), rs2234693 (ESR1) и rs1801275 (IL4R) для прогнозирования риска развития ХОБЛ.Выводы. Полученные в ходе настоящего исследования данные могут помочь в понимании наследственной предрасположенности к ХОБЛ и прогнозировании развития этого заболевания на основе анализа полиморфизма генов и их межгенных взаимодействий. Introduction. Chronic obstructive pulmonary disease (COPD) is a multifactorial disease, which is characterized by the development on the base of single nucleotide polymorphisms in the structure of the genes encoding pathogenetically significant protein molecules.Purpose. To study the association of gene polymorphisms of proteins involved in the pathogenesis of the disease with the risk of COPD development in the Belarusian population.Materials and methods. The polymerase chain reaction method was used to genotype polymorphic loci of the genes rs4508917 (CXCL10), rs2280788 (CCL5), rs2228014 (CXCR4), rs333 (CCR5), rs1801275 (IL4R), rs2243250 (IL4956), IL68900s (TNF-α), rs2234693 (ESR1), and rs731236 (VDR) in 95 people withCOPD and 95 healthy volunteers. The comparative analysis of the genotype frequency distribution between the groups of patients with COPD and healthy individuals was carried out using the SPSS program based on the assessment of the χ2 and Fisher’s exact test. The odds ratios were calculated to determine the contribution of genotypes associated with the development of COPD in creating a predisposition to the disease. The analysis of gene-gene interactions was performed using the MDR program.Results. It was found that the carriage of the homozygous genotype containing the A allele of the rs1800896 (IL10) polymorphic variant is associated with the increased risk of COPD. In relation to the studied groups, the association of heterozygous genotypes of the rs2280788 (CCL5) and rs2234693 (ESR1) polymorphisms was determined with the increased risk of the disease development. The genotypes of polymorphic loci rs1800795 (IL6) and rs1801275 (IL4R) with minor alleles are associated with reduced susceptibility to COPD by the dominant genetic model. Analysis of gene- gene interactions revealed the risk and protective combinations of genotypes of the studied genes in relation to the COPD. The study revealed the significance of the combined effect of rs1800795 (IL6), rs1800896 (IL10), rs2234693 (ESR1). and rs1801275 (IL4R) polymorphism genes to predict the risk of COPD development.Conclusions. The obtained data can help in understanding the hereditary predisposition to COPD and predicting the development of this disease on the base of analysis of genetic polymorphisms and their gene-gene interactions.

557 Background: BC risk assessment is important for guiding personalized screening and risk-reducing interventions. TCv8 is used to estimate BC risk based on age, breast density, family cancer history and other clinical factors. Accuracy may be improved by combining TCv8 with a PRS. We developed and validated a PRS for diverse ancestries based on 149 common genetic variants (PRS-149) comprised of 56 ancestry-informative and 93 BC-associated variants. Here, we describe a BC risk model that combines PRS-149 with TCv8. Methods: Subjects had multigene panel testing for hereditary cancer and were negative for pathogenic variants in known BC susceptibility genes. A combined risk score (CRS), incorporating PRS-149 and TCv8, was developed based on 189,230 women, including 43,444 (23%) with a history of BC. Breast Imaging Reporting and Data System (BI-RADS) breast density measurements were available for 12,363 women. We used multivariable logistic regression to test breast density and PRS-149 for association with risk of BC. An independent test cohort of 6,030 BC-unaffected women with BI-RADS assessment was used to evaluate the effect of PRS-149 on risk stratification. Relative contributions of family history, breast density, other clinical factors in TCv8 and PRS-149 were examined by adding terms sequentially to an ANOVA model. We compared differences in classification of women as high (20%) or low/moderate (20%) remaining lifetime risk according to TCv8 versus CRS. Results: In the development cohort, increased breast density was significantly associated with higher risk of BC (p=3.0x10-6) with an effect size consistent with TCv8. PRS-149 improved BC risk prediction over age, breast density and family history (OR per unit standard deviation: 1.41, 95% CI: 1.37 – 1.46; p: 1.8x10-105). PRS-149 was weakly but significantly correlated with both family history (r=0.09) and breast density (r=0.01). After adjusting for multiple testing, no other factors were correlated with PRS-149. In the independent test cohort, PRS-149 explained 27% of CRS variability after accounting for family history, breast density and other clinical factors. Adding PRS-149 to TCv8 significantly altered risk estimates, with 16.3% (983/6,030) of patients classified differently by CRS versus TCv8. By TCv8 alone, 38.0% (2,289/6,030) of patients were classified as high-risk. Among patients who were high-risk by TCv8, 25.2% (576/2,289) were downgraded by CRS. Conclusions: This is the first BC risk model that includes breast density, family history, and a PRS based on genetically determined ancestry that is validated for diverse populations. Addition of PRS-149 improved risk prediction and substantially modified risk stratification compared to TCv8 alone. Implementation of CRS may therefore lead to improved identification of women who are likely to benefit from increased surveillance and preventive medications.

The article presents the essence and operational potential of the information and analysis system supporting the decision making process within the framework of security-related policing operations. This system is being developed by a scientific consortium led by the Police Academy, Szczytno. The project finance is provided by the National Centre for Research and Development. The main element to ensure the effectiveness of the system in question will be an application with a planning and decision mechanism and prediction algorithms. The above mentioned algorithms are designed to provide information on the probability of success of police operations and on the necessary costs which must be incurred in a given crisis situation in order to implement their individual, expected variants. Using historical data and algorithms developed on its basis, the system is supposed to indicate the relevant forces and resources required, the methods and tactics for operations and characteristics of the security infrastructure. Moreover, the publication presents the fundamental mechanisms of the police command and control process during emergency situations and general remarks regarding the professional development of those who manage these types of policing operations. In the author’s opinion, of particular importance in this respect is the course addressed to commissioned police officers trained to be commanders or deputy commanders of security-related policing operations, where classes are conducted using a simulator for police operations in emergency situations. It is a form of advanced command staff training with the use of a virtual computer simulation system. The simulator makes it possible to develop algorithms for dealing with crisis incidents and to improve the command process during emergencies. One of the practical goals of developing the information and analysis system is its integration with the simulator for police operations in emergency situations. In this respect, it is supposed to be a tool used in multimedia decision-making training. The author comes to the conclusion that the expected functionalities of the information and analysis system will have a positive effect both on the educational process of improving professional qualifications of commanders of security-related policing operations and on the real planning, implementation and assessment of the operations themselves.

Abstract Background : Survival prediction in essential thrombocythemia (ET) and polycythemia vera (PV) is currently based on clinically-derived risk variables, including age, thrombosis history and leukocyte count (Blood. 2012;120:1197; Leukemia. 2013;27:1874). We have previously reported on the prognostic contribution of mutations, in both ET and PV (Blood Adv. 2016;1:21). The current study examines the possibility of integrating genetic and clinical information for predicting overall (OS), leukemia-free (LFS) and myelofibrosis-free (MFFS) survival in ET and PV. Methods : Study patients were recruited from the Mayo Clinic, Rochester, MN, USA and the University of Florence, Florence, Italy, based on availability of next-generation sequencing (NGS)-derived mutation information. Diagnoses were according to the 2016 World Health Organization criteria (Blood. 2016;127:2391). NGS-detected coding region variants were filtered through the Exome Aggregation Consortium (ExAC) database and annotated by the Catalogue of Somatic Mutations in Cancer (COSMIC) database as mutants or variants of uncertain significance (VUS). Conventional statistics was employed for outcome analysis and assessment of model performance. Results: 906 molecularly-annotated patients (416 from Mayo and 490 from Florence), including 502 ET and 404 PV cases, were included in the current study. The Mayo/Florence cohorts included 270/232 ET (median age 57/54 years, 60%/59% females) and 146/258 PV (median age 63/58 years, 52%/44% females) patients; median follow-up was 9.9/12.9 years for ET and 10.7/12.4 years for PV; during this time 39%/38% deaths and 4.4%/6.5% leukemic and 16%/33% fibrotic progressions were documented for ET, with the corresponding figures for PV being 50%/26%, 4.8%/3% and 13%/36%. Cytogenetic information was available in 84%/63% ET and 80%/49% PV cases in the Mayo/Florence cohorts. In both Mayo and Florence cohorts, multivariable analysis of mutations identified primarily spliceosome mutations to adversely affect OS (SF3B1 and SRSF2 in ET and SRSF2 in PV) and MFFS (U2AF1 and SF3B1 in ET); in addition, TP53 mutations was associated with leukemic transformation in ET, in both patient cohorts. Other mutations with independently significant contribution, validated in one but not both cohorts, included EZH2 (OS and LFS in ET), IDH2 (OS and LFS in PV) and RUNX1 (LFS in PV and ET). For the purposes of the current study, mutations considered "adverse" for subsequent analysis and development of prognostic models required validation in both Mayo and Florence cohorts. Age-adjusted, all-inclusive multivariable analysis of genetic and clinical variables identified the following as independent risk factors for OS, in both Mayo and Florence cohorts: ET ─ SRSF2/SF3B1 mutations, age >60 years and male sex; PV ─ SRSF2 mutations, age >67 years and leukocyte count ≥11 x 109/l. In addition, multivariable analysis flagged leukocytosis in ET (Florence cohort only) and abnormal karyotype in PV (Mayo cohort only) as additional factors. Development of mutation-enhanced international prognostic systems for ET and PV In order to optimize the number of informative cases, the two Mayo and Florence databases were subsequently combined and subjected to multivariable analysis that confirmed the independent survival effect, in ET, of SRSF2/SF3B1 mutations (HR 2.8, 95% CI 1.8-4.3), age >60 years (HR 6.7, 95% CI 4.8-9.4) and male sex (HR 1.8, 95% CI 1.4-2.4) and, in PV, of SRSF2 mutations (HR 7.0, 95% CI 2.3-17.4), age >60 years (HR 5.7, 95% CI 3.3-10.1), and leukocyte count ≥11 x 109/l (HR 2.4, 95% CI 1.5-3.9); the combined analysis also flagged independent prognostic contribution from abnormal karyotype in PV (HR 2.1, 95% CI 1.1-3.6). HR-weighted risk point allocation resulted in new, mutation-enhanced 4-tiered risk models for ET (MIPSS-ET based on mutations, age and sex; figure 1a) and PV (MIPSS-PV based on mutations, karyotype, leukocyte count and age; figure 1b). Both models displayed high predictive accuracy and were internally validated by bootstrapping. The combined analysis also confirmed the impact of TP53 mutations on LFS (figure 1c) and U2AF1/SF3B1 mutations on MFFS (figure 1d), in ET. Conclusions: Spliceosome mutation information enhances survival prediction in ET and PV and identifies those at risk for fibrotic progression. TP53 mutations predict leukemic transformation in ET. Disclosures No relevant conflicts of interest to declare.

1579 Background: Current clinical prediction models provide syndrome-specific numeric estimates of an individual's likelihood of having a specific hereditary cancer syndrome (e.g., PREMM5 for Lynch syndrome; BRCAPRO for BRCA1/2). With the emergence of multigene panel testing (MGPT), there is a need to evaluate individuals' risk of carrying a pathogenic variant in a diverse array of cancer susceptibility genes in parallel. This study’s aim was to develop and validate the PREMMplus clinical prediction model for multigene cancer risk assessment. Methods: PREMMplus was developed in a cohort of 7296 individuals who had undergone germline MGPT at a single center. Logistic regression models were used to examine candidate predictive variables – including age, sex, ethnicity, and personal/family history of cancer – to provide a numeric estimate of an individual’s likelihood of carrying a pathogenic/likely pathogenic germline variant in one of 18 cancer susceptibility genes (11 high- [ APC, BRCA1/2, CDH1, EPCAM, MLH1, MSH2, MSH6, biallelic MUTYH, PMS2, and TP53] and 7 moderate-penetrance [ ATM, CDKN2A, CHEK2, PALB2, PTEN, RAD51C, and RAD51D]). Model performance was validated in an independent dataset of 14845 individuals who had undergone MGPT at a commercial laboratory. Results: Using clinical characteristics, including personal/family history of 18 cancers plus colorectal adenoma burden, PREMMplus demonstrated an excellent ability to predict pathogenic variants in high penetrance genes at 90% sensitivity. PREMMplus had acceptable performance with the addition of 7 moderate penetrance genes. PREMMplus was well-calibrated and demonstrated comparable performance in the external validation dataset. Conclusions: PREMMplus is the first validated risk assessment model to quantify an individual’s likelihood of carrying pathogenic variants in a wide diversity of cancer risk genes, and can be used to select individuals who should undergo MGPT. As expected, PREMMplus’s discriminatory capacity was reduced with the inclusion of moderate penetrance cancer risk genes. [Table: see text]

The human genome is a source of information for researchers that study complex diseases with the perspective of a better understanding of the pathologies and the development of new therapeutic strategies. Starting from the beginning of the current century, a growing number of technologies devoted to DNA sequencing have emerged, generally referred to as Next Generation Sequencing (NGS) technologies. NGS gradually decreased the cost of sequencing a human genome to around US$1000, enabling the use of these technologies for clinical and research purposes, such as Genome-wide association studies (GWAS). GWAS studies have enlightened the presence of disease- associated loci, in particular variants that could be used to evaluate the risk of an individual to develop a disease. Unfortunately, different sources of errors are able to impair the interpretation and use of NGS data: on the one hand, we have noise related to the process of DNA sequencing and read alignment errors, which could lead to false positive calls or artifacts. On the other hand, variants could be poor predictors for the manifestation of their associated disease. Nowadays the challenge of genomic data interpretation has driven the research towards the development of methods for the analysis and interpretation of genomic variations, eventually predicting the probability of a patient to develop a definite disease. A fair evaluation of these tools is essential to understand the applicability of the presented methods in clinical practice. The Critical Assessment of Genome Interpretation (CAGI) has been developed with the aim of defining the current state of art in terms of methods for predicting the impact of genomic changes at molecular and phenotype levels. CAGI is a community-driven experiment in which different prediction methods, developed by a set of invited groups, are evaluated on a common dataset. Unfortunately, no common guidelines were given to evaluate the tools presented in CAGI experiments, this has made the comparison between different CAGI experiments cumbersome, since different mathematical indexes and scripts have been used to evaluate the involved methods. My PhD project has been focused on the development of software for the assessment of machine learning methods in regression and multiple phenotype challenges. This tool is based on state of the art assessment principles, derived from literature or previous CAGI experiments. This software is available as an R package and has been used to repeat or perform new assessments on a wide range of CAGI experiments. The knowledge acquired during the development of this project was used to evaluate two CAGI 5 challenges: Pericentriolar Material 1 (PCM1) and Intellectual Disability (ID) panel. The experience I have acquired, through the development of all previously mentioned works, has led the improvement and assessment of a machine learning method. In particular, I have developed a software for the prediction of cholesterol levels, based on genotype data. Eventually I have tested the reliability of this method. This tool was the milestone in a project founded by the Italian Ministry of Health.
Il genoma umano è una risorsa ricca di informazioni per i ricercatori che si dedicano allo studio delle patologie complesse. L’obiettivo di questo genere di ricerche è giungere ad una migliore comprensione di queste malattie e quindi sviluppare nuove strategie terapeutiche per la cura dei pazienti affetti. Dall’inizio di questo secolo, un numero crescente di tecnologie per il sequenziamento del DNA sono state sviluppate, sono conosciute come tecnologie “Next Generation Sequencing” (NGS). Le tecnologie NGS hanno gradualmente diminuito il costo del sequenziamento di un genoma umano fino a circa 1000 dollari, ciò ha consentito l’utilizzo di questi strumenti nella pratica clinica e nella ricerca, in particolare negli studi di associazione genome-wide o “Genome-wide association studies” (GWAS). Questi lavori hanno portato alla luce l’associazione di alcune varianti con alcune patologie o caratteri complessi. Queste varianti potrebbero essere utilizzate per valutare il rischio che un individuo sviluppi una particolare patologia. Sfortunatamente diverse sorgenti di errore sono in grado di ostacolare l’uso e l’interpretazione dei dati genomici: da una parte abbiamo il rumore legato al processo di sequenziamento e gli errori di allineamento delle reads. Dall’altra parte gli SNP non sempre possono essere utilizzati in modo affidabile per predire l’insorgenza della malattia a cui sono stati associati. Il Critical Assessment of Genome Interpretation è stato organizzato con l’obiettivo di definire lo stato dell’arte nei metodi che stimano l’effetto di variazioni genetiche a livello molecolare o fenotipico. Negli anni il CAGI ha dato vita a più competizioni in cui diversi gruppi di ricerca hanno testato i loro metodi di predizione su diversi dataset condivisi. L’assenza di linee generali su come condurre la valutazione delle performance dei predittori, ha reso difficile un confronto fra metodi sviluppati in edizioni diverse del CAGI. In questo contesto, il progetto di dottorato si è focalizzato nello sviluppo di un software per la valutazione di metodi di apprendimento automatici basati sulla regressione o la predizione di fenotipi multipli. Questo strumento si fonda su criteri di analisi della performance, derivanti dalla letteratura e da precedenti esperimenti del CAGI. Questo software è stato sviluppato in R ed utilizzato per ripetere o valutare ex novo la qualità dei predittori in un gran numero di esperimenti del CAGI. Le conoscenze acquisite durante lo sviluppo di questo progetto, sono state utilizzate per valutare due competizioni del CAGI 5: la Pericentriolar Material 1 (PCM1) e il Pannello per le Disabilità Intellettive (ID). L’esperienza derivante dal completamento dei lavori precedentemente elencati, ha guidato lo sviluppo e il miglioramento delle prestazioni di un metodo predittivo. In particolare è stato sviluppato un software per la predizione dei livelli di colesterolo, basato su dati genotipici, di cui è stata testata la validità con criteri matematici allo stato dell’arte. Questo strumento è stato la pietra portante di un progetto fondato dal Ministero della Salute Italiano.

The utilization of in vitro tests with a tiered testing strategy for detection of mild ocular irritants can reduce the use of animals for testing, provide mechanistic data on toxic effects, and reduce the uncertainty associated with dose selection for clinical trials. The first section of this thesis describes how in vitro methods can be used to improve the prediction of the toxicity of chemicals and ophthalmic products. The proper utilization of in vitro methods can accurately predict toxic threshold levels and reduce animal use in product development. Sections two, three and four describe the development of new sensitive in vitro methods for predicting ocular toxicity. Maintaining the barrier function of the cornea is critical for the prevention of the penetration of infections microorganisms and irritating chemicals into the eye. Chapter 2 describes the development of a method for assessing the effects of chemicals on tight junctions using a human corneal epithelial and canine kidney epithelial cell line. In Chapter 3 a method that uses a primary organ culture for assessing single instillation and multiple instillation toxic effects is described. The ScanTox system was shown to be an ideal system to monitor the toxic effects over time as multiple readings can be taken of treated bovine lenses using the nondestructive method of assessing for the lens optical quality. Confirmations of toxic effects were made with the utilization of the viability dye alamarBlue. Chapter 4 describes the development of sensitive in vitro assays for detecting ocular toxicity by measuring the effects of chemicals on the mitochondrial integrity of bovine cornea, bovine lens epithelium and corneal epithelial cells, using fluorescent dyes. The goal of this research was to develop an in vitro test battery that can be used to accurately predict the ocular toxicity of new chemicals and ophthalmic formulations. By comparing the toxicity seen in vivo animals and humans with the toxicity response in these new in vitro methods, it was demonstrated that these in vitro methods can be utilized in a tiered testing strategy in the development of new chemicals and ophthalmic formulations.

The risks assessment is described by the action of estimating the probability distribution functions of possible successes or failures of a system during a given prediction period. Typical probabilistic predictive models and methods for solving risks prediction problems are described, and their classification is given. Priority development directions for risks prediction in standard system processes and their implementation procedures are proposed. The reported examples demonstrate the effects and interpretation of the predictive results obtained. Notes: 1. System is a combination of interacting elements organized to achieve one or more stated purposes (according to ISO/IEC/IEEE 15288 “Systems and software engineering—System life cycle processes”). 2. Risk is defined as the effect of uncertainty on objectives considering consequences. An effect is a deviation from the expected — positive and/or negative (according to ISO Guide 73).

With the rapid development of offshore wind energy in Europe, a large number of piled structures are being installed. In areas with sandy seabed conditions, erosion of sediment by the actions of wave and current can negatively influence foundation capacity. An accurate prediction model of scour around the piles is therefore required. Well-accepted scour prediction methods exist; both for the equilibrium scour depth and the time scale of scour [1] around single piles. These standard formulas have been combined with metocean data and a hindcasting model to calculate the expected scour depth around piles of wind turbine tripod foundations. Other causes of scour, such as pile-pile interaction, effect of proximity of structural members to the seabed, and seabed mobility were also assessed in order to determine the amount of global scour to be considered. The scour predictions were compared to measurements taken at an offshore wind turbine foundation at Park Alpha Ventus (PAV) in the German North Sea [2]. The data showed very good agreement with the measured scour around the piles. Both the equilibrium scour depth and time scale of scour were well predicted using the hindcasting model. The measured scour below the central column of the tripod structure exceeded expectations; this is believed to be due to a pumping effect during storm episodes. Finally, the effect of scour on the vertical effective stress around the tripod piles was assessed with a finite element model. Local scour had an important effect while scour below the centre of the structure had a much more limited effect. Considering the combined effects of multiple pile interaction, scour below the central column, and making an allowance for seabed mobility, an equivalent global scour depth for pile capacity calculations was established.

Lifespan assessment of flexible risers involves the evaluation of fatigue parameters, requiring accurate predictions of stresses and their variation in pipe components. For predicting the effect of complex three-dimensional nonlinear dynamics on component stress histories, multi-scale methods can combine generality of application with computational efficiency. In this paper, we describe the development of a two-scale computational homogenisation procedure linking a coarse-scale analysis model using specialised beam elements, and a detailed stress prediction model consisting of a pipe section with components modelled with shell elements and frictional contact interactions. To use the procedure, the detailed model first functions as a virtual test rig, by which parameters of the global model may be determined. For detailed stress prediction, the global model is tested under the operating conditions of interest providing a set of generalised strains which are applied to the detailed model. The models are implemented in the general-purpose finite-element package Abaqus. As key aspects of the procedure, we show how generalised stresses and strains can be imposed on the detailed model uniformly without introducing spurious boundary effects and demonstrate how local stresses can be determined using strain data from the global model.

Abstract The main objective and mission of the European project ATLAS+ (Advanced Structural Integrity Assessment Tools for Safe Long Term Operation) are to address the remaining technology gaps for the safe and long term operation of nuclear reactor pressure coolant boundary systems. This project includes the development and validation of advanced simulation tools based on fracture mechanics methods using physically based mechanistic models. In the Work Package 3 (WP3), benchmark calculations using different available models are conducted to investigate the accuracy and the capability of the different models for ductile crack growth of different constraint condition, such as laboratory specimens and piping structure, which were tested in the Work Package 1 (WP 1). The authors joined the WP3 activity and investigated the effect of the parameters of the GTN (Gurson-Tvergaard-Needleman) model on the fracture behavior of the specimens. In this paper, the parameters of the GTN model were calibrated to simulate the fracture behavior of CT specimens, notched tensile (NT) specimens and single edge notched tensile (SENT) specimens of ferritic pipe material and the applicability of the GTN model. The adjusted parameters by the CT specimen predicted the fracture behavior of the SENT specimens, but did not those of the NT specimens. The adjusted parameters by the CT specimens were applied to the piping structure mock-up and they predicted the maximum load in high accuracy.

Abstract The effect of an LWR environment on fatigue life is currently assessed using methods (such as NUREG/CR-6909) that may be excessively conservative when applied to plant components and loading transients. To reduce this conservatism, the ASME Working Group for Environmental Fatigue Evaluation Methods (WG-EFEM) has proposed the development of an improved assessment methodology for environmental fatigue based on a Total Life Prediction approach that would be adequately, but not excessively, conservative. Such an approach necessitates the development of analytical methods for the various stages of crack nucleation, short crack growth and long crack growth. Hence, there is a requirement to undertake testing within the short crack growth regime that would bridge the gap between fatigue nucleation and long crack growth (Paris Law) enabling better prediction of total life measured by fatigue endurance. Previous negative R long crack growth testing using corner-crack specimens measured the effects of crack closure under compressive loading, and has been used to address some of the conservatism in existing assessment methods. This methodology has been developed further to enable negative R short crack growth testing with in-situ monitoring using DCPD. Testing has been undertaken in both high temperature air (300°C) and a simulated PWR primary water chemistry at 300°C on both cold-worked and non-cold-worked stainless steel specimens at a load ratio of R = −1. One heat of stainless steel has been tested, with another heat of different grain size to be tested imminently, in order to investigate the effect of grain size on short crack growth rates. FEA modelling has been undertaken to both correlate Direct Current Potential Drop (DCPD) response with crack growth measurements, and to determine the effective stress intensity factor ranges applied under the loading conditions based on the specific material properties. This paper describes the methodology and findings from this negative R short crack growth test programme. Crack growth rates have been compared to ASME Code Sec. XI and Code Case N-809 reference curves and results from material specific in-house testing to assist the understanding of the behaviour of mechanically short cracks.

Abstract The effect of environment on fatigue life is currently assessed using methods (such as NUREG/CR-6909) that may be excessively conservative when applied to plant components and loading transients. To reduce this conservatism, the ASME WG-EFEM has proposed the development of an improved assessment methodology for environmental fatigue based on a Total Life Prediction approach that would be adequately, but not excessively, conservative. Such an approach necessitates the development of analytical methods for the various stages of crack nucleation, short crack growth and long crack growth. Hence, there is a requirement to undertake testing within the short crack growth regime that would bridge the gap between fatigue nucleation and long crack growth (Paris Law) enabling better prediction of total life measured by fatigue endurance. A test methodology has been developed by Wood to enable short crack growth testing with in-situ monitoring using DCPD. Testing has been undertaken in both high temperature air (300°C) and simulated end-of-cycle primary water chemistry at 300°C on cold-worked stainless steel specimens, which were subject to a range of load ratios and rise times. FEA modelling has been undertaken to determine the effective stress intensity factors applied under the loading conditions based on the specific material properties. This paper presents the results from a testing program conducted with EPRI, to measure fatigue crack growth data for short cracks from 0.15 mm to 1.0 mm. Crack growth rates have been compared to those predicted in ASME, Code Case N-809 and results from material specific in-house testing to assist the understanding of the behaviour of mechanically short cracks.

This article presents a systematic procedure and Artificial Neural Networks (ANN) based tool for comfort objectification and customer classification, to support drive train developer during the product development process. In this case, the term “comfort objectification” can be clarified as reproduction of subjectively sensed convenience of a passenger through objectively measurable values. Many factors, such as noise, vibration, physical or psychological condition of a passenger generally influence the ride comfort. The main purpose of this project is to develop the drive train and his assemblies which can sustain customers’ demand of vibration comfort. The presented methods enable the identification and the evaluation of vehicle dynamic properties from the passengers’ point of view during start-up, shifting, steering as well as other procedures in the early stage of the product development process. For instance, this tool is developed for the evaluation of ride comfort during a start-up of a front-drive, intermediate-class car. To estimate the subjective sensation, the new driver modeling tool based on ANN is developed from the way individual drivers make their assessment. This paper presents a user-friendly interface which allows both experts and users who are still short of experience in the ANN field, to create different network structures depending on the task. By means of this tool, the modeling process can be effectively simplified and shortened. As a result, the objective values captured during each drive test are efficiently correlated with the subjective sensation. Consequently, the high performance of comfort prediction can be achieved. By using self organizing map as a tool for driver classification, the different types of drivers can be considered due to their comfort expectation and style of driving. The comfort prediction concerning each driver group can then be carried out. According to the approach of virtual drive train development, in this study, the elaborated multi-body simulation models are primarily used to generate several virtual start-up processes. This enables the determination of NVH properties of the future product and allows the developer to investigate the effect of vibration like judder and jerking on the degree of ride comfort. By applying objective data from the simulation, the comfort assessment using the presented tools can be executed. In the long run, costly drive tests and cost-intensive prototypes can be partially replaced.