Submitted by Ana Maria Fiscina Sampaio (fiscina@bahia.fiocruz.br) on 2012-11-27T19:16:53Z No. of bitstreams: 1 Fabio David Couto Estudo da prevalencia... 2002.pdf: 44946029 bytes, checksum: 5521f6983cf2f27b55c924fff532ed06 (MD5) / Made available in DSpace on 2012-11-27T19:16:53Z (GMT). No. of bitstreams: 1 Fabio David Couto Estudo da prevalencia... 2002.pdf: 44946029 bytes, checksum: 5521f6983cf2f27b55c924fff532ed06 (MD5) Previous issue date: 2002 / Fundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, Bahia, Brasil / O metabolismo da fiomocisteina pode ser afetado por carência nutricional de vitaminas (Be, B12 e folatos) ou por alterações genéticas que afetam o funcionamento de enzimas envolvidas em sua via metabólica. A homozigose para a mutação C677T no gene da enzima metilenotetrahidrofolato redutase (MTHFR) tem sido relacionada com a hiperhomocisteinemia, descrita como fator de risco importante e Independente para a ocorrência de doenças cardiovasculares. As hemoglobinopatias estruturais, principalmente a hemoglobina S, também tem sido associada a estes eventos. No presente estudo foi determinada a prevalência da mutação C677T da MTHFR, por PCR e RFLP, em 843 recém-nascidos de Salvador-Bahia, correlacionando a presença desta mutação com o perfil de hemoglobinas determinado por HPLC. Os níveis séricos de homocisteína, vitamina Bi2 e folatos foram determinados em um subgrupo de 75 recém-nascidos, com os diferentes genótipos para o polimorfismo C677T da MTHFR: 25 selvagens (C/C), 25 heterozigotos (C/T) e 25 homozigotos (T/T) mutantes, todos portadores de hemoglobina AA. A freqüência do alelo T foi de 23,4%, com prevalências de 36,2% da heterozigose e 5,3% da homozigose para o polimorfismo C677T da MTHFR. O alelo T foi normalmente distribuído entre os gêneros (p = 0,206) e entre os diferentes genótipos de hemoglobinas p = 0,696. Diferenças estatísticas nâo foram encontradas para os níveis de homocisteína, folatos e vitamina B12 entre os diferentes genótipos do polimorfismo C677T da MTHFR. Contudo as análises estratificadas para os níveis de folatos e vitamina B12 demonstraram que os recém-nascidos com níveis destas vitaminas abaixo dos valores medianos e portadores dos genótipos C/T e T/T apresentaram maior freqüência entre os neonatos com níveis de homocisteína acima de 6,7 |amol/L. Também foram encontradas diferenças estatisticamente significantes entre os pesos dos recém- nascidos e os níveis de folatos (p = 0,043). Nossa população apresenta freqüência elevada do alelo T do polimorfismo C677T da MTHFR associada as hemoglobinopatias estruturais, o que pode influenciar na incidência das doenças vasculares freqüentemente observadas entre os portadores de hemoglobinopatias estruturais. De acordo com os resultados, os folatos são poderosos preditores dos níveis de homocisteína assim como do peso dos recém-nascidos, independente da mutação C677T; contudo, este efeito é potencializado pela presença da homozigose do alelo T. / The homocysteine metabolism is affected by nutritional status of B12 and folate vitamins or can results from genetics mutations of genes responsable for proteins expression involved in re-methylation or trans-sulphuration metabolism pathway. A common mutation, C677T, in the methylenetetrahydrofolate reductase gene (MTHFR) reduces the MTHFR activity and increase the total homocysteine serum levels (tHcy). Hyperhomocysteinaemia has been identified as a risk factor for cardiovascular disease as established for variant hemoglobins. Here we investigated the C677T mutation prevalence in MTHFR gene by PCR and RFLP techniques, in 843 neonates from Salvador-Bahia-Brazil, and its coexistence with variant hemoglobins, which was determinated by HPLC. We estimated homocysteine, B12, and folate vitamins serum levels concentrations by chemiluminescence in a subgroup of 75 neonates with hemoglobin AA pattern, carriers different genotypes for MTHFR polimorphism: 25 wide type (C/C), 25 heterozygous (C/T), and 25 mutant homozygous (T/T). The mutant allele frequency was 0.23. Among heterozygous and mutant homozygous states the prevalence for polymorphism C677T of MTHFR gene were 36.2% and 5.3%, respectively. No gender (p = 0.206) or hemoglobin genotypes (p = 0,696) related differences were observed for T allele distribution, even for homocysteine, folate, and B12 vitamin levels among different MTHFR polymorphism. Stratified analysis for B12 vitamins or folate levels showed high frequency of newborns C/T and T/T with homocysteine levels above 6.7 |imol/L in the groups of B12 vitamin and folate levels below of it median values. Statistical differences was found in newborns with low folate serum levels and weight according to them with it serum levels above of it median value (p = 0.043). The 672 studied newborn population had high frequency of T allele associated with variant hemoglobins. It become important once may contribute for occlusive vascular disease development. Our results showed relationship among folate and homocysteine serum levels, that folate is an important homocysteine serum levels predictor as well newborns weight, and this effect can be enhanced by T allele homozygouse

Submitted by Marlene Santos (marlene.bc.ufg@gmail.com) on 2016-08-01T17:22:48Z No. of bitstreams: 3 Dissertação - Heloisa Ribeiro Storchilo - 2016.pdf: 1886092 bytes, checksum: 0d827ee8679247c63f79b15ce325d19b (MD5) ata de aprovação mestrado - Heloisa Ribeiro Storchilo - 2016.pdf: 1216009 bytes, checksum: 6475e6eeeb9d106946f78b578c1bfa34 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2016-08-02T12:04:36Z (GMT) No. of bitstreams: 3 Dissertação - Heloisa Ribeiro Storchilo - 2016.pdf: 1886092 bytes, checksum: 0d827ee8679247c63f79b15ce325d19b (MD5) ata de aprovação mestrado - Heloisa Ribeiro Storchilo - 2016.pdf: 1216009 bytes, checksum: 6475e6eeeb9d106946f78b578c1bfa34 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2016-08-02T12:04:36Z (GMT). No. of bitstreams: 3 Dissertação - Heloisa Ribeiro Storchilo - 2016.pdf: 1886092 bytes, checksum: 0d827ee8679247c63f79b15ce325d19b (MD5) ata de aprovação mestrado - Heloisa Ribeiro Storchilo - 2016.pdf: 1216009 bytes, checksum: 6475e6eeeb9d106946f78b578c1bfa34 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2016-06-16 / Toxoplasma gondii is a protozoan which presents a high worldwide prevalence. This parasite is able to pass the placental barrier which results in fetal infection with severe sequelae. The diagnostics of the congenital infection is complex and should be performed precociously. The newborn screening detects several diseases in the newborns (NB) and the implantation of the toxoplasmosis detection in this set of exams enables the precocious detection of this disease. Therefore the aim of this study was to perform the toxoplasmosis serologic triage (IgM and IgG) in blood collected in filter paper; to evaluate and compare the sensitivity of serologic analysis from peripheric blood collected in filter paper; to perform confirmatory serologic tests (IgM and IgG) and complementary (PCR) to confirm the NB with serologic indication of congenital toxoplasmosis and to speed the precocious diagnostics of congenital toxoplasmosis in NB blood. At the moment of the newborn screening blood collection a second sample of blood was collected in filter paper from NB attended in Clinics Hospital from the Federal University of Goias, Maternity Hospital Dona Iris both located in Goiania, Goias, and Cais Nova Era located in Aparecida de Goiania, Goias. These samples were processed and ELISA test was performed. The NB which presented results with absorbance titers equal or higher than 3.0 were submitted to a new peripheric blood collection alongside with the blood collection from their mothers and the PCR technique was performed as to confirm the congenital infection. A total of 949 blood samples were collected in filter paper and 432 (45.52%) were IgG positive while 1 (0.10%) was IgM positive. In the IgG positive NB (432/949) which presented ELISA titers ≥ 3.0; 104 pairs of peripheric blood were analyzed. From these 104 samples of peripheric blood, 5 pairs (4.80%) presented IgG and IgM negative results, four (3.84%) presented discrepant results, i.e., NB sample negative and mother sample IgG positive, in 95 pairs (91.34%) there were accordant results with both IgG positives. The PCR technique was performed in the 95 samples of IgG positive children and was possible to detect the parasite’s DNA in one sample of NB peripheric blood. Therefore these results show that the inclusion of the toxoplasmosis serologic test in the newborn screening, which is already performed in SUS to detect other diseases, demonstrated to be effective in the precocious detection of T. gondii infected NB. We highlight that succeed in the infected NB triage several criteria should be taken into account and that a greater sampling should be performed as to ratify these results. / Toxoplasma gondii é um protozoário de elevada prevalência na população mundial. O parasito pode atravessar a barreira transplacentária, resultando em infecção fetal com graves sequelas. O diagnóstico da infecção congênita é complexo e deve ser realizado precocemente. O teste do pezinho detecta patologias em recém-nascidos, dessa forma a implementação do diagnóstico de toxoplasmose nesse conjunto de exames possibilita a detecção precoce dessa doença. Este estudo teve como objetivo: Realizar triagem sorológica para toxoplasmose (IgM e IgG) em sangue coletado em papel filtro; avaliar e comparar a sensibilidade da sorologia em papel filtro com a sorologia realizada com sangue periférico; comparar a concentração de anticorpos detectada pela sorologia do sangue periférico dos recém-nascidos com os resultados de suas respectivas mães; realizar testes sorológicos confirmatórios (IgM e IgG) e complementares como PCR na confirmação dos recém-nascidos com indicação de infecção congênita e dinamizar o diagnóstico precoce da toxoplasmose congênita no sangue de recém-nasidos. Foi coletada uma segunda amostra de sangue em papel filtro de crianças atendidas no Hospital das Clínicas da Universidade Federal de Goiás, Hospital Maternidade Dona Íris, Goiânia, Goiás e Cais Nova Era, Aparecida de Goiânia, Goiás, quando as mesmas foram realizar o teste do pezinho, e realizado o teste de Elisa. Os recém-nascidos que apresentaram resultados com índices de absorbância maiores ou iguais a 3.0 foram submetidos à coleta de sangue periférico, tanto das mães quanto de seus respectivos filhos. Em todas as amostras de sangue periférico dos recém-nascidos foi realizada a técnica de PCR para confirmação de infecção congênita. Do total de 949 amostras de sangue coletadas em papel filtro, detectou-se em 432 (45,52%) amostras a presença de IgG e uma (0,10%) foi detectada a presença IgM. Nos recém-nascidos reagentes para IgG (432/949) que apresentaram índice ≥3,0 pela técnica de Elisa foram realizados 104 pares de coletas de sangue periférico, incluindo mãe e filho. Das 104 amostras de sangue periférico dos recém-nascidos, nove (8,65%) não apresentaram IgG anti-T.gondii e 95 (91,34%) apresentaram resultado positivo para IgG, concordando com os resultados encontrados anteriormente em papel filtro. Dos 104 pares de amostras de sangue periférico, cinco pares (4,80%) tiveram resultados negativos para IgG e IgM, em quatro pares (3,84%), os resultados foram discrepantes, sendo a amostra da criança negativa e a da mãe IgG positivo, em 95 pares (91,34%) das amostras analisadas, foram concordantes na detecção de IgG. Foi realizada a técnica de PCR nas 95 amostras de sangue periférico das crianças com sorologia confirmada e foi possível detectar o DNA do parasito em uma amostra de sangue periférico dos recém-nascidos. Diante dos resultados obtidos nesse trabalho, a adição da sorológica para toxoplasmose ao teste do pezinho que já é disponibilizado pelo SUS para outras infecções, se mostrou eficaz na detecção precocemente de recém-nascidos infectados pelo T. gondii. Salientamos que para se obter êxito na triagem dos recém-nascidos infectados, vários critérios deverão ser considerados, e que uma amostragem maior devera ser analisada para ratificar os resultados obtidos.

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Biomarker testing, wherein the concentration of a biochemical marker is measured to predict the presence or absence of a certain binary characteristic (e.g., a disease) in a subject, is an essential component of public health screening. For many diseases, the concentration of disease-related biomarkers may exhibit a wide range, particularly among the disease positive subjects, in part due to variations caused by external and/or subject-specific factors. Further, a subject's actual biomarker concentration is not directly observable by the decision maker (e.g., the tester), who has access only to the test's measurement of the biomarker concentration, which can be noisy. In this setting, the decision maker needs to determine a classification scheme in order to classify each subject as test negative or test positive. However, the inherent variability in biomarker concentrations and the noisy test measurements can increase the likelihood of subject misclassification. We develop an optimal data-driven framework, which integrates optimization and data analytics methodologies, for subject classification in disease screening, with the aim of minimizing classification errors. In particular, our framework utilizes data analytics methodologies to estimate the posterior disease risk of each subject, based on both subject-specific and external factors, coupled with robust optimization methodologies to derive an optimal robust subject classification scheme, under uncertainty on actual biomarker concentrations. We establish various key structural properties of optimal classification schemes, show that they are easily implementable, and develop key insights and principles for classification schemes in disease screening. As one application of our framework, we study newborn screening for cystic fibrosis in the United States. Cystic fibrosis is one of the most common genetic diseases in the United States. Early diagnosis of cystic fibrosis can substantially improve health outcomes, while a delayed diagnosis can result in severe symptoms of the disease, including fatality. We demonstrate our framework on a five-year newborn screening data set from the North Carolina State Laboratory of Public Health. Our study underscores the value of optimization-based approaches to subject classification, and show that substantial reductions in classification error can be achieved through the use of the proposed framework over current practices. / Doctor of Philosophy / A biomarker is a measurable characteristic that is used as an indicator of a biological state or condition, such as a disease or disorder. Biomarker testing, where a biochemical marker is used to predict the presence or absence of a disease in a subject, is an essential tool in public health screening. For many diseases, related biomarkers may have a wide range of concentration among subjects, particularly among the disease positive subjects. Furthermore, biomarker levels may fluctuate based on external factors (e.g., temperature, humidity) or subject-specific characteristics (e.g., weight, race, gender). These sources of variability can increase the likelihood of subject misclassification based on a biomarker test. We develop an optimal data-driven framework, which integrates optimization and data analytics methodologies, for subject classification in disease screening, with the aim of minimizing classification errors. We establish various key structural properties of optimal classification schemes, show that they are easily implementable, and develop key insights and principles for classification schemes in disease screening. As one application of our framework, we study newborn screening for cystic fibrosis in the United States. Cystic fibrosis is one of the most common genetic diseases in the United States. Early diagnosis of cystic fibrosis can substantially improve health outcomes, while a delayed diagnosis can result in severe symptoms of the disease, including fatality. As a result, newborn screening for cystic fibrosis is conducted throughout the United States. We demonstrate our framework on a five-year newborn screening data set from the North Carolina State Laboratory of Public Health. Our study underscores the value of optimization-based approaches to subject classification, and show that substantial reductions in classification error can be achieved through the use of the proposed framework over current practices.

The primary purpose of newborn screening is to quickly identify children that are at risk of having a specific disorder in order to start treatment, prevent early death and reduce the chances of permanent physical or mental damage. The current and widely accepted approach used for identification of metabolism disorders involves a flow injection analysis with mass spectrometry detection of acylcarnitines and amino acids. Although this approach is widely accepted and has shown to be sufficient for identification of multiple metabolism disorders the method is not fully quantitative and results often have to be confirmed by second-tier tests. The primary focus of this research was to improve the accuracy and selectivity of this screening method by employing a high resolution chromatographic separation for the combined analysis of twelve acylcarnitines and seven amino acids. This method is an improvement over the current methodology allowing for separation of key isomers that are diagnostic for different metabolism disorders, reducing the need for multiple second-tier tests to confirm results and shortening the time to diagnosis. In order to further improve the efficiency of newborn screening we developed an in-line desorption device, which allows for direct analysis of DBS eliminating the need for punching disks from the filter paper cards. Our device was the first published paper that demonstrated the ability to directly analyze dried blood spots, without the need for any offline sample processing. Using this device, we validated a method to quantify biomarkers related to Maple Syrup Urine Disease, a disorder that requires a second-tier test for confirmation. To further improve the accuracy of dried blood spot analysis we evaluated a technique to correct the sample volume in low and high hematocrit samples. The level of hematocrit in blood spotted on filter paper cards affects the volume of sample analyzed, leading to errors in accuracy. Diffuse reflectance was used to relate differences in sample hematocrit on dried blood spots. We validated our technique with eighteen donor samples at various levels of hematocrit. Correcting sample volume for hematocrit showed improved precision and accuracy over the standard approach, ultimately reducing the potential to misidentify samples.

Public health screening plays an important role in the overall healthcare system. As an example, consider newborn screening, a state-level initiative that screens newborns for life-threatening genetic disorders for which early treatment can substantially improve health outcomes. Another topical example is in the realm of infectious disease screening, e.g., screening for COVID-19. The common features of both public health screening problems include large testing populations and resource limitations that inhibit screening efforts. Cost is a major barrier to the inclusion of genetic disorders in newborn screening, and thus screening must be both highly accurate and efficient; and for COVID-19, limited testing kits, and other shortages, have been major barriers to screening efforts. Further, for both newborn screening and infectious disease screening, equity (reducing health disparities among different sub-populations) is an important consideration. We study the testing process design for newborn screening for genetic diseases, considering cystic fibrosis as a model disorder. Our optimization-based models take into account disease-related parameters, subject risk factors, test characteristics, parameter uncertainty, and limited testing resources so as to design equitable, accurate, and robust screening processes that classify newborns as positive or negative for cystic fibrosis. Our models explicitly consider the trade-off between false-negatives, which lead to missed diagnoses, and the required testing resources; and the trade-off between the accuracy and equity of screening. We also study the testing process design for infectious disease screening, considering COVID-19 as a model disease. Our optimization-based models account for key subject risk factors that are important to consider, including the likelihood of being disease-positive, and the potential harm that could be averted through testing and the subsequent interventions. Our objectives include the minimization of harm (through detection and mitigation) or maximization of testing coverage. These are complex problems. We develop novel mathematical models and characterize key structural properties of optimal solutions. This, in turn, allows the development of effective and efficient algorithms that exploit these structural properties. These algorithms are either polynomial- or pseudo-polynomial-time algorithms, and are able to solve realistic-sized problems efficiently. Our case studies on cystic fibrosis screening and COVID-19 screening, based on realistic data, underscore the value of the proposed optimization-based approaches for public health screening, compared to current practices. Our findings have important implications for public policy. / Doctor of Philosophy / Public health screening plays an important role in the overall healthcare system. As an example, consider newborn screening, a state-level initiative that screens newborns for life-threatening genetic disorders for which early treatment can substantially improve health outcomes. Another topical example is in the realm of infectious disease screening, e.g., screening for COVID-19. The common features of both public health screening problems include large testing populations and resource limitations that inhibit screening efforts. Cost is a major barrier to the inclusion of genetic disorders in newborn screening, and thus screening must be both highly accurate and efficient; and for COVID-19, limited testing kits, and other shortages, have been major barriers to screening efforts. Further, for both newborn screening and infectious disease screening, equity (reducing health disparities among different sub-populations) is an important consideration. We study the testing process design for newborn screening for genetic diseases, considering cystic fibrosis as a model disorder. Our optimization-based models take into account disease-related parameters, subject risk factors, test characteristics, parameter uncertainty, and limited testing resources so as to design screening processes that classify newborns as positive or negative for cystic fibrosis. Our models explicitly consider the trade-off between false-negatives, which lead to missed diagnoses, and the required testing resources; and the trade-off between the accuracy and equity of screening. We also study the testing process design for infectious disease screening, considering COVID-19 as a model disease. Our optimization-based models account for key subject risk factors that are important to consider, including the likelihood of being disease-positive, and the potential harm that could be averted through testing and the subsequent interventions. Our objectives include the minimization of harm (through detection and mitigation) or maximization of testing coverage. These are complex problems. We develop novel mathematical models and characterize key structural properties of optimal solutions. This, in turn, allows the development of effective and efficient algorithms that exploit these structural properties. Our case studies on cystic fibrosis screening and COVID-19 screening, based on realistic data, underscore the value of the proposed optimization-based approaches for public health screening, compared to current practices. Our findings have important implications for public policy.

Newborn screening programs measure analyte levels in neonatal blood spots to identify individuals at high risk of disease. Carnitine and acylcarnitine levels are primary markers used in the detection of fatty acid oxidation disorders. These analytes may be influenced by certain pre/perinatal or newborn screening related factors. The primary objective of this study was to explore the association between these characteristics and levels of blood carnitines and acylcarnitines in the newborn population. The study was composed of two parts: a systematic review and a clinical database analysis of existing newborn screening data. The systematic review results suggested considerable variability across studies in the presence and directionality of associations between analyte levels and birth weight, gestational age, age at time of blood spot collection, type of sample, and storage time. Sex was not significantly associated with carnitine or acylcarnitine levels in neonatal blood. We identified a need to more fully investigate a potential interaction between gestational age and birth weight in regard to analyte levels. The secondary data analyses indicated a statistically significant relationship between analyte levels and all perinatal / infant and newborn screening related factors of interest, but effect sizes were generally small. The interaction between gestational age and birth weight was significant in all models; when further explored through graphical analysis with conditional means, extremely premature neonates stood out as having distinct analyte patterns in relation to birth weight. Variation in the ratio of total acylcarnitine to free carnitine was better accounted for by the perinatal and newborn factors than was variation in any individual carnitine or acylcarnitine, indicating that proportions of carnitine and acylcarnitines may be more important in understanding an individual’s metabolic functioning than individual analyte levels. A low proportion of variation was explained in all multivariate models, supporting the use of universal algorithms in newborn screening and suggesting the need for further large scale empirical research targeted at previously unaccounted for perinatal factors such as birth stress.

Newborn screening programs measure analyte levels in neonatal blood spots to identify individuals at high risk of disease. Carnitine and acylcarnitine levels are primary markers used in the detection of fatty acid oxidation disorders. These analytes may be influenced by certain pre/perinatal or newborn screening related factors. The primary objective of this study was to explore the association between these characteristics and levels of blood carnitines and acylcarnitines in the newborn population. The study was composed of two parts: a systematic review and a clinical database analysis of existing newborn screening data. The systematic review results suggested considerable variability across studies in the presence and directionality of associations between analyte levels and birth weight, gestational age, age at time of blood spot collection, type of sample, and storage time. Sex was not significantly associated with carnitine or acylcarnitine levels in neonatal blood. We identified a need to more fully investigate a potential interaction between gestational age and birth weight in regard to analyte levels. The secondary data analyses indicated a statistically significant relationship between analyte levels and all perinatal / infant and newborn screening related factors of interest, but effect sizes were generally small. The interaction between gestational age and birth weight was significant in all models; when further explored through graphical analysis with conditional means, extremely premature neonates stood out as having distinct analyte patterns in relation to birth weight. Variation in the ratio of total acylcarnitine to free carnitine was better accounted for by the perinatal and newborn factors than was variation in any individual carnitine or acylcarnitine, indicating that proportions of carnitine and acylcarnitines may be more important in understanding an individual’s metabolic functioning than individual analyte levels. A low proportion of variation was explained in all multivariate models, supporting the use of universal algorithms in newborn screening and suggesting the need for further large scale empirical research targeted at previously unaccounted for perinatal factors such as birth stress.