BRPI0903187B1 - method for predicting the clinical response of a dengue virus infected patient during the first days after symptom onset, a method for diagnosing dengue virus infection, and a kit for determining the prognosis of the clinical response of a dengue infected patient - Google Patents
method for predicting the clinical response of a dengue virus infected patient during the first days after symptom onset, a method for diagnosing dengue virus infection, and a kit for determining the prognosis of the clinical response of a dengue infected patient Download PDFInfo
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- BRPI0903187B1 BRPI0903187B1 BRPI0903187A BRPI0903187A BRPI0903187B1 BR PI0903187 B1 BRPI0903187 B1 BR PI0903187B1 BR PI0903187 A BRPI0903187 A BR PI0903187A BR PI0903187 A BRPI0903187 A BR PI0903187A BR PI0903187 B1 BRPI0903187 B1 BR PI0903187B1
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Abstract
marcadopes prognósticos de pesposta clínica de pacientes infectados com vírus da dengue a invenção se refere a um método para fornecer o prognóstico de resposta clínica de pacientes infectados com o vírus da dengue conduzido através da análise da expressão de um grupo de genes, bem como polimorfismo alélico e níveis de proteínas codificadas por eles através do seguintes métodos: microarranjos de dna, nortbern blot, pcr, pcr quantitativa, western blot, elisa e citometria de fluxo, o uso de qualquer dos métodos acima referidos, ou outros relacionados, é a base para desenvolvimento de kíts preditores de resposta clínica, desta forma facilitando o manejo clínico.Clinical response prognostic markers of dengue virus infected patients The invention relates to a method for providing prognosis of clinical response of dengue virus infected patients conducted by analyzing the expression of a gene group as well as allelic polymorphism and protein levels encoded by them by the following methods: dna microarray, nortbern blot, pcr, quantitative pcr, western blot, elisa and flow cytometry, the use of any of the above or related methods is the basis for development of predictive clinical response kits, thus facilitating clinical management.
Description
MÉTODO DE PREDIÇÃO DA RESPOSTA CLÍNICA DO PACIENTE INFECTADO PE1O VÍRUS DA DENGUE DURANTE OS PRIMEIROS DIAS APÓS O INÍCIO DOS SINTOMAS, MÉTODO DE DIAGNÓSTICO DE INFECÇÃO PELO VÍRUS DA DENGUE, E, KIT PARA DETERMINAR O PROGNÓSTICO DA RESPOSTA CLÍNICA DO PACIENTE INFECTADO POR DENGUEMETHOD OF PREDICTING THE CLINICAL RESPONSE OF THE PATIENT INFECTED DENGUE VIRUS DURING THE FIRST DAYS AFTER THE START OF SYMPTOMS, DIAGNOSTIC METHOD OF INFECTING THE DENGUE VIRUS, AND, KIT TO DETERMINE THE PROGNOSTIC OF THE PROGNOSIS
Esta invenção diz respeito a prognósticos para a resposta clínica de pacientes infectados pelo vírus da dengue, baseados no nível de expressão dos genes listados nas Tabelas 2-7, ou em suas proteínas codificadas, bem como polimorfismo alélico, em amostras biológicas.This invention relates to prognoses for the clinical response of patients infected with the dengue virus, based on the level of expression of the genes listed in Tables 2-7, or on their encoded proteins, as well as allelic polymorphism, in biological samples.
FUNDAMENTOS DA INVENÇÃOBACKGROUND OF THE INVENTION
O vírus da dengue é um membro da família Flaviviridae, gênero flavivírus com guatro sorotipos antigenicamente distintos (DENV-1 a DENV-4). A infecção pelo vírus da dengue é um problema de saúde pública mundial, com uma incidência estimada em 50-100 milhões de casos de febre do dengue (FD ou dengue clássica), resultando em 500.000 casos clínicos de febre hemorrágica do dengue com risco de vida (FHD ou dengue hemorrágica) e 24.000 mortes por ano (Green e Rothman 2006). A FHD é caracterizada por vasculopatia, o gue leva a um extravasamento plasmático súbito gue reduz o volume sanguíneo e pode resultar em chogue hipovolêmico, o gue é conhecido como Síndrome de Chogue do Dengue (SCD) . Não há nenhuma terapia antiviral para o tratamento da infecção por dengue nem meios para impedir o desenvolvimento da FHD.The dengue virus is a member of the family Flaviviridae, a genus flavivirus with four antigenically distinct serotypes (DENV-1 to DENV-4). Dengue virus infection is a worldwide public health problem, with an estimated incidence of 50-100 million cases of dengue fever (FD or classic dengue), resulting in 500,000 life-threatening clinical cases of dengue hemorrhagic fever (DHF or hemorrhagic dengue) and 24,000 deaths per year (Green and Rothman 2006). DHF is characterized by vasculopathy, which leads to a sudden plasma leak which reduces blood volume and can result in hypovolemic chog, which is known as Dengue Chog Syndrome (SCD). There is no antiviral therapy for the treatment of dengue infection and no means to prevent the development of DHF.
Durante a fase aguda da infecção, os pacientes com FD e FHD têm guadros clínicos muito similares. No entanto, a defervescência (depois de 2 a 7 dias do início dos sintomas) é acompanhada por sinais de perturbações circulatórias em pacientes com FHD (OMS 1999) . Por isso, acreditamos gue a assinatura genética diferenciando as duas diferentes formasDuring the acute phase of infection, patients with DF and DHF have very similar clinical guidelines. However, defervescence (2 to 7 days after the onset of symptoms) is accompanied by signs of circulatory disturbances in patients with DHF (WHO 1999). Therefore, we believe that the genetic signature differentiates the two different forms
Petição 870180125506, de 03/09/2018, pág. 7/13 clinicas de dengue poderia ser uma ferramenta poderosa a ser usada em áreas endêmicas para prever a resposta do paciente, facilitando o manejo clinico.Petition 870180125506, of 9/3/2018, p. 7/13 dengue clinics could be a powerful tool to be used in endemic areas to predict the patient's response, facilitating clinical management.
O conceito atualmente aceito como subjacente à imunopatologia da FHD se apóia na sequência de infecção e indução de anticorpos não-neutralizantes (Endy, Nisalak et al. 2004; Pang, Cardosa et al. 2007), bem como na ativação de clones de célula T reativa-cruzada (MANGADA, Endy et al. 2002; Mongkolsapaya, Dejnirattisai et al. 2003; MANGADA Rothman e 2005; Mongkolsapaya, Duangchinda et al. 2006) ambos adquiridos após a infecção primária. Alguns dos marcadores de gravidade encontrados no sangue periférico, que foram correlacionados com o extravasamento plasmático na FHD incluem citocinas inflamatórias, quimiocinas e moléculas de aderência expressas em níveis elevados (Green, Vaughn et al. 1999; Juffrie, van der Meer et al. 2000; Mustafa, ElbishbishiThe concept currently accepted as underlying the immunopathology of DHF is based on the infection and induction of non-neutralizing antibodies (Endy, Nisalak et al. 2004; Pang, Cardosa et al. 2007), as well as on the activation of T cell clones. cross-reactive (MANGADA, Endy et al. 2002; Mongkolsapaya, Dejnirattisai et al. 2003; MANGADA Rothman and 2005; Mongkolsapaya, Duangchinda et al. 2006) both acquired after primary infection. Some of the severity markers found in peripheral blood, which have been correlated with plasma leakage in DHF include inflammatory cytokines, chemokines and adhesion molecules expressed at high levels (Green, Vaughn et al. 1999; Juffrie, van der Meer et al. 2000 ; Mustafa, Elbishbishi
frequência das células ativadas (Green, Vaughn et al. 1999; Azeredo, De Oliveira-Pinto et al. 2006) e ocorrência de apoptose (Mongkolsapaya, et al Dejnirattisai. 2003; Myint, Endy et al. 2006). Estas descobertas contribuíram para o avanço da compreensão dos mecanismos imunológicos envolvidos no desenvolvimento da FHD, mas não foi provado que nenhuma delas seja confiável ou útil como marcador biológico para uso clínico.frequency of activated cells (Green, Vaughn et al. 1999; Azeredo, De Oliveira-Pinto et al. 2006) and occurrence of apoptosis (Mongkolsapaya, et al Dejnirattisai. 2003; Myint, Endy et al. 2006). These findings contributed to the advancement of the understanding of the immunological mechanisms involved in the development of DHF, but none of them has been proven to be reliable or useful as a biological marker for clinical use.
O microarranjo de DNA tem sido utilizado como uma ferramenta para localizar assinaturas genéticas e prever com sucesso a resposta clínica do paciente com câncer (van deThe DNA microarray has been used as a tool to locate genetic signatures and successfully predict the clinical response of the cancer patient (van de
Vijver, He et al. 2002; Chen, infecções bacterianas e viraiVijver, He et al. 2002; Chen, bacterial and viral infections
Scherer, Magness et al. 2007)Scherer, Magness et al. 2007)
prognóstico de 70 genes, relataram o uso de perfil previamente associado com o risco de metástase distante precoce em pacientes jovens com câncer de mama cujos linfonodos foram negativos para a presença de células cancerosas, como um instrumento de orientação para a terapia adjuvante nesses doentes (van deprognosis of 70 genes, reported the use of a profile previously associated with the risk of distant early metastasis in young patients with breast cancer whose lymph nodes were negative for the presence of cancer cells, as an instrument of guidance for adjuvant therapy in these patients (van in
Desta forma, melhora-se a seleçãoIn this way, the selection is improved
Vijver, He et al. 2002).Vijver, He et al. 2002).
de pacientes que iriam se beneficiar com o tratamento adjuvante sistêmico, reduzindo as taxas tanto de tratamento excessivo como de subtratamento.of patients who would benefit from systemic adjuvant treatment, reducing rates of both overtreatment and undertreatment.
No modelo de infecção de dengue, o padrão de expressão gênica foi caracterizado junto com a fase de infecção em pessoas acometidas com a forma mais grave da doença, em duas diferentes coortes de dengue: Simmons et al. (2007) mostraram uma assinatura molecular em Células Mononucleares do Sangue Periférico (PBMCs), representando as fases aguda e convalescente da Síndrome de Choque do Dengue e eles relataram que os transcritos gênicos para 24 genes estimulados por IFN foram menos abundantes em adultos (6 pacientes) com síndrome de choque do dengue do que em 8 pacientes com dengue sem SCD, enquanto que genes envolvidos em apoptose estavam expressos em maior quantidade (Simmons, Popper et al. 2007). Recentemente Ubol et al (2008) em uma coorte de crianças da Tailândia confirmaram conceitualmente os resultados mostrados neste relatório e no estudo vietnamita, associando a diminuição da resposta imune inata e o aumento da apoptose com o desenvolvimento de FHD (Ubol, Masrinoul et al. 2008), mas o padrão genético difere do que 5 mostramos aqui. Uma possível razão pode ser a faixa etária utilizada, na medida em que sabe-se que fenotipicamente o repertório da resposta imune é diferente durante os primeiros anos, onde predomina a resposta inata, comparativamente aos adultos (Pettiford, Jason et al. 2002). Em contraste, Kruif 10 et al. (2008) relataram uma associação geral da gravidade do dengue e maior quantidade de expressão dos genes envolvidos na resposta imune inata (de Kruif, Setiati et al. 2008).In the dengue infection model, the pattern of gene expression was characterized along with the stage of infection in people affected with the most severe form of the disease, in two different dengue cohorts: Simmons et al. (2007) showed a molecular signature in Peripheral Blood Mononuclear Cells (PBMCs), representing the acute and convalescent phases of Dengue Shock Syndrome and they reported that gene transcripts for 24 IFN-stimulated genes were less abundant in adults (6 patients ) with dengue shock syndrome than in 8 dengue patients without SCD, while genes involved in apoptosis were expressed in greater quantities (Simmons, Popper et al. 2007). Recently Ubol et al (2008) in a cohort of children from Thailand conceptually confirmed the results shown in this report and in the Vietnamese study, associating the decrease in the innate immune response and the increase in apoptosis with the development of DHF (Ubol, Masrinoul et al. 2008), but the genetic pattern differs from the 5 we show here. A possible reason may be the age group used, as it is known that the repertoire of the immune response is phenotypically different during the first years, where the innate response predominates, compared to adults (Pettiford, Jason et al. 2002). In contrast, Kruif 10 et al. (2008) reported a general association of the severity of dengue and a greater amount of expression of the genes involved in the innate immune response (de Kruif, Setiati et al. 2008).
Vários exames laboratoriais de dengue baseados em sorologia ou detecção viral estão disponíveis e são capazes 15 de confirmar o diagnóstico de infecção de dengue. Quando utilizados separadamente, cada um desses exames têm limitações, porém, quando utilizados nas combinações corretas, é possível confirmar ou afastar com segurança o diagnóstico de infecção pelo vírus da dengue. No entanto, a maior 20 limitação no manejo clínico de casos de dengue é a capacidade do clínico avaliar o risco de um determinado paciente infectado de dengue desenvolver os seus sintomas fatais e a sua real necessidade de ser hospitalizado. A incidência de FHD é de aproximadamente 1% e é fatal se não for tratada 25 rapidamente. Mesmo sob assistência médica a taxa de mortalidade devido a FHD pode atingir 10 a 20%. Infelizmente a maior parte dessas mortes poderíam ser evitadas com os cuidados médicos adequados. Um dos principais culpados da falta de assistência adequada é o caos causado pelos grandes surtos. A Organização Mundial de Saúde (OMS) estabeleceu critérios clínicos para definir os casos de FHD, mas as dificuldades tanto para preencher esses critérios como para identificar precocemente os casos graves, fazem com que o 5 manejo clínico das formas graves da doença se torne um desafio até mesmo maior (Bandyopadhyay, Lum et al. 2006; Deen, Harris et al. 2006). Por isso, a busca de novas ferramentas para prever a resposta clínica do paciente é essencial para facilitar a avaliação da necessidade de intervenções médicas.Several laboratory tests for dengue based on serology or viral detection are available and are capable of confirming the diagnosis of dengue infection. When used separately, each of these tests has limitations, however, when used in the correct combinations, it is possible to safely confirm or rule out the diagnosis of dengue virus infection. However, the biggest limitation in the clinical management of dengue cases is the clinician's ability to assess the risk of a particular dengue infected patient developing their fatal symptoms and their real need to be hospitalized. The incidence of DHF is approximately 1% and is fatal if it is not treated quickly 25. Even under medical assistance, the mortality rate due to DHF can reach 10 to 20%. Unfortunately, most of these deaths could be prevented with proper medical care. One of the main culprits of the lack of adequate assistance is the chaos caused by the large outbreaks. The World Health Organization (WHO) has established clinical criteria to define cases of DHF, but the difficulties both in meeting these criteria and in identifying serious cases early, make the clinical management of severe forms of the disease a challenge. even greater (Bandyopadhyay, Lum et al. 2006; Deen, Harris et al. 2006). Therefore, the search for new tools to predict the patient's clinical response is essential to facilitate the assessment of the need for medical interventions.
SUMÁRIO DA INVENÇÃOSUMMARY OF THE INVENTION
A presente invenção consiste num método de avaliar a resposta clinica do paciente infectado com o virus da dengue durante a fase aguda da infecção e antes de surgirem os sinais de vasculopatia. 0 método consiste na análise dos 15 niveis de expressão de um grupo de genes (Tabelas 2-7), ou proteínas codificadas por eles, assim como polimorfismos alélicos.The present invention consists of a method of evaluating the clinical response of the patient infected with the dengue virus during the acute phase of the infection and before the signs of vasculopathy appear. The method consists of analyzing the 15 levels of expression of a group of genes (Tables 2-7), or proteins encoded by them, as well as allelic polymorphisms.
Num aspecto da invenção, a predição da resposta clínica dos pacientes infectados com o vírus da dengue é baseada na 20 análise de expressão dos 73 genes mostrados na Tabela 6, originados pela combinação dos melhores 200 genes mais significativos (menor valor p) e 200 maiores diferenças na expressão (magnitude fold change) entre dengue clássica e dengue hemorrágica.In one aspect of the invention, the prediction of the clinical response of patients infected with the dengue virus is based on the expression analysis of the 73 genes shown in Table 6, originated by the combination of the best 200 most significant genes (lowest p value) and 200 largest differences in expression (magnitude fold change) between classic dengue and hemorrhagic dengue.
Num outro aspecto da invenção, os genes na Tabela 2 são usados para caracterização e diferenciação da expressão gênica em pessoas infectadas com vírus da dengue (FD + FHD) de outras causas de doenças febris (não dengue ou ND).In another aspect of the invention, the genes in Table 2 are used to characterize and differentiate gene expression in people infected with dengue virus (FD + FHD) from other causes of febrile illnesses (not dengue or ND).
Ainda um aspecto da invenção, diz respeito ao uso da Análise de Discriminação Linear, como regra de classificação, e resubstituição potencializada (bolstered resubstitution), como estimador de erro, de genes na forma isolada, dupla, trio ou mais genes para predizer resposta clínica de pacientes infectados com vírus da dengue.Still an aspect of the invention, concerns the use of Linear Discrimination Analysis, as a classification rule, and bolstered resubstitution, as an error estimator, of genes in isolated, double, trio or more genes to predict clinical response of patients infected with dengue virus.
Em outro aspecto da invenção, a expressão de duplas de genes baseados na lista de 1981 genes (Tabela 7) é usada como classificador para predizer resposta clínica de pacientes infectados com vírus da dengue.In another aspect of the invention, the expression of gene pairs based on the 1981 gene list (Table 7) is used as a classifier to predict the clinical response of patients infected with dengue virus.
Em outro aspecto da invenção, a expressão de trio de genes baseados na lista de 1981 genes (Tabela 7) é usada como classificador para predizer resposta clínica de pacientes infectados com vírus da dengue.In another aspect of the invention, the expression of a trio of genes based on the 1981 gene list (Table 7) is used as a classifier to predict the clinical response of patients infected with dengue virus.
Em outro aspecto da invenção, a expressão de quarteto de genes baseados na lista de 1981 genes (Tabela 7) é usada como classificador para predizer resposta clínica de pacientes infectados com vírus da dengue.In another aspect of the invention, the expression of a quartet of genes based on the 1981 gene list (Table 7) is used as a classifier to predict the clinical response of patients infected with dengue virus.
Em ainda um outro aspecto da invenção, a avaliação da expressão gênica pode ser realizada por qualquer das técnicas destinadas a detectar RNA, cDNA, cRNA (PCR, RT-PCR, PCR quantitativa, microarranjo de DNA, Northern biotting e outros).In yet another aspect of the invention, the evaluation of gene expression can be performed by any of the techniques designed to detect RNA, cDNA, cRNA (PCR, RT-PCR, quantitative PCR, DNA microarray, Northern biotting and others).
Em ainda um outro aspecto da invenção, a avaliação dos níveis dos produtos proteicos codificados pelos genes mostrados na Tabela 7 pode ser realizada por qualquer técnica destinada a detectar formas desnaturadas e nativas das proteínas (ELISA, Western biotting, dot-blotting, citometria de fluxo e outros).In yet another aspect of the invention, the levels of protein products encoded by the genes shown in Table 7 can be evaluated by any technique designed to detect denatured and native forms of proteins (ELISA, Western biotting, dot-blotting, flow cytometry) and others).
ιι
BREVE DESCRIÇÃO DAS FIGURASBRIEF DESCRIPTION OF THE FIGURES
FIG. 1 mostra medidas de ruído e eficiência. A seta indica o único arranjo, no grupo não dengue, que mostrou reduzida tanto a relação sinal/ruído quanto percentagem de chamadas presentes.FIG. 1 shows measures of noise and efficiency. The arrow indicates the only arrangement in the non-dengue group, which showed a reduced both signal / noise ratio and percentage of calls present.
FIG. 2 é um gráfico de degradação de RNA.FIG. 2 is a graph of RNA degradation.
FIG. 3 mostra a análise exploratória dos dados baseados nos 1981 genes selecionados. (A) dendrograma de agrupamento hierárquico. (B) Gráfico MDS 2-D. (C) Gráfico MDS 3-D. AFIG. 3 shows the exploratory analysis of the data based on the 1981 selected genes. (A) hierarchical clustering dendrogram. (B) MDS 2-D chart. (C) MDS 3-D chart. THE
hierárquico (apenas os 40 melhores genes). (C) Gráfico MDS 3D (apenas os 40 melhores genes) .hierarchical (only the best 40 genes). (C) 3D MDS chart (only the 40 best genes).
FIG. 5 mostra o classificador para o par de genes PSMB9 e MT2A, na discriminação de FD contra FHD. Menor expressão de ambos os genes é característica de FHD, enquanto maior expressão de ambos os genes é característica de FD. A probabilidade estimada de erro para este classificador é de apenas 5.38%.FIG. 5 shows the classifier for the PSMB9 and MT2A gene pair, in the discrimination of FD against FHD. Lesser expression of both genes is characteristic of FHD, while greater expression of both genes is characteristic of FD. The estimated probability of error for this classifier is only 5.38%.
FIG. 6 mostra níveis de expressão de genes para discriminação entre pacientes FD e FHD. (A) para todos os genes testados, os ensaios de pPCR foram realizados usando uma mistura de 8 pacientes FD e 8 FHD usados no ensaio de microarranjos. (B) Para todos os genes, os ensaios de qPCR foram realizados para um grupo de 8 amostras FD e 8 FHD usados no ensaio de microarranjo (coluna branca), ou um grupo de 8 amostras FD e 8 FHD independentes (coluna cinza) . O experimento foi realizado duas vez e cada grupo foi analisado em triplicata.FIG. 6 shows levels of gene expression for discrimination between FD and FHD patients. (A) for all genes tested, the pPCR assays were performed using a mixture of 8 FD and 8 FHD patients used in the microarray assay. (B) For all genes, qPCR assays were performed for a group of 8 FD and 8 FHD samples used in the microarray assay (white column), or a group of 8 independent FD and 8 FHD samples (gray column). The experiment was carried out twice and each group was analyzed in triplicate.
FIG. 7 fornece gráficos Vulcões mostrando os valores p correlacionados com a magnitude de diferença de expressão (fold change) em pacientes FD versus FHD e casos de dengue (FD+FHD) versus não dengue. Os genes destacados em vermelho e azul representam os 40 melhores genes de acordo com os valores p e magnitude de diferença de expressão respectivamente.FIG. 7 provides Volcanoes graphs showing the p-values correlated with the magnitude of the difference of expression (fold change) in patients FD versus FHD and cases of dengue (FD + FHD) versus non-dengue. The genes highlighted in red and blue represent the 40 best genes according to the p values and magnitude of difference of expression respectively.
DESCRIÇÃO DETALHADA DA INVENÇÃODETAILED DESCRIPTION OF THE INVENTION
A tecnologia de microarranjos de DNA é uma importante ferramenta todos os para estudar a expressão de RNAm simultaneamente de genes num genoma. Esta tecnologia consiste de milhares de diferentes sequências deDNA microarray technology is an important tool to study the expression of mRNA simultaneously from genes in a genome. This technology consists of thousands of different sequences of
DNA representando diferentes genes adsorvidos em regiões conhecidas de uma matriz sólida, tais como lâmina de vidro.DNA representing different genes adsorbed in known regions of a solid matrix, such as a glass slide.
As lâminas podem ser hibridizadas com sondas derivadas de RNAm de células ou tecidos. Arranjos de oligonucleotidios (composto por DNA deThe slides can be hybridized with probes derived from cell or tissue mRNA. Oligonucleotide arrays (composed of DNA from
25-mers) se baseia na estratégia do pareamento perfeito/despareamento (match/mismatch) da sonda no chip de25-mers) is based on the probe's perfect match / mismatch
DNA, onde são usadas sondas que pareiam perfeitamente (match) e sondas que diferem da primeira por uma base em seu centro (mismatch) e que por isso não hibridizam ao chip de DNA. Neste tipo de microarranjo, apenas um fluorocromo é usado para marcação do RNA complementar (RNAc) e o sinal é detectado usando um equipamento de escaneamento óptico. A quantificação da sonda hibridizada é realizada comparando os sinais dos oligos mismatch (hibridização não especifica) e os oligos que pareiam perfeitamente (match).DNA, where probes that match perfectly are used and probes that differ from the first by a base in its center (mismatch) and that therefore do not hybridize to the DNA chip. In this type of microarray, only one fluorochrome is used to mark the complementary RNA (cRNA) and the signal is detected using optical scanning equipment. Quantification of the hybridized probe is carried out by comparing the signals of the oligos mismatch (hybridization not specified) and the oligos that look perfectly (match).
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II
Microarranjos de DNA tem sido usado como ferramenta para achar assinaturas gênicas e predizer com sucesso a resposta clinica de pacientes com câncer (van de Vijver, He et al. 2002; Chen, Yu et al. 2007) assim como para infecções bacterianas e virais (Ramilo, Allman et al. 2007; Scherer, Magness et al. 2007). van de Vijver et al (2002) relataram o uso de perfil prognóstico usando 70 genes como ferramenta para guiar a terapia adjuvante nesses pacientes através da seleção daqueles pacientes que realmente se beneficiariam desse tratamento adjuvante sistêmico e reduzindo tanto a taxa de tratamento excessivo ou subtratamento. Os 70 genes utilizados por esses autores foram previamente associados com risco de metástase distante em pacientes jovens com câncer de mama e cujo linfonodos foram negativos para a presença de células cancerosas (van de Vijver, He et al. 2002).DNA microarrays have been used as a tool to find gene signatures and successfully predict the clinical response of cancer patients (van de Vijver, He et al. 2002; Chen, Yu et al. 2007) as well as for bacterial and viral infections ( Ramilo, Allman et al. 2007; Scherer, Magness et al. 2007). van de Vijver et al (2002) reported the use of a prognostic profile using 70 genes as a tool to guide adjuvant therapy in these patients by selecting those patients who would really benefit from this systemic adjuvant treatment and reducing both the rate of overtreatment or undertreatment. The 70 genes used by these authors were previously associated with a risk of distant metastasis in young patients with breast cancer and whose lymph nodes were negative for the presence of cancer cells (van de Vijver, He et al. 2002).
Há muitas evidências que fatores genéticos, envolvidos em susceptibilidade/resistência à doenças infecciosas, influenciam a resposta imune em humanos. Esses fatores são complexos e geneticamente controlados e não seguem um perfil de herança Mendeliana (Clementi and Di Gianantonio 2006). Alguns desses fatores identificados por microarranjos de DNA são envolvidos com alteração da regulação gênica e algumas vezes devido a polimorfismos que interferem com a expressão gênica de várias formas, seja diretamente se ligando ao promotor, seja interferindo na cascata de sinais que interfere com a ativação gênica. Polimorfismo genético do hospedeiro relacionado com resposta imune tem sido mostrado estar correlacionado com expressão gênica alterada e susceptibilidade a desenvolver FHD, tais como o alelo TNF-308, associado com elevados níveis de TNFa, tem sido correlacionado com aumentado risco de desenvolver a forma mais grave da doença (Fernandez-Mestre, Gendzekhadze et al. 2004; Soundravally and Hoti 2007) . Uma associação tem sido recentemente relatada entre o genótipo selvagem ΆΆ MBL2, altos níveis de MBL e alto risco de desenvolver trombocitopenia associado com infecção pelo vírus da dengue (Acioli-Santos, Segat et al. 2008). Por outro lado, polimorfismo no promotor de CD209 (Sakuntabhai, Turbpaiboon et al. 2005), foi associado com reduzida expressão de DC-SIGN e, possivelmente, reduzida susceptibilidade de células dendriticas a infecção pelo vírus da dengue. Portanto, a procura por alteração na expressão gênica entre diferentes quadros clínicos de dengue usando microarranjos de DNA pode elucidar em alta escala os fatores genéticos e mecanismos imunopatológicos relacionados com gravidade da dengue.There is much evidence that genetic factors, involved in susceptibility / resistance to infectious diseases, influence the immune response in humans. These factors are complex and genetically controlled and do not follow a Mendelian inheritance profile (Clementi and Di Gianantonio 2006). Some of these factors identified by DNA microarrays are involved with alteration of gene regulation and sometimes due to polymorphisms that interfere with gene expression in various ways, either directly binding to the promoter, or interfering with the signal cascade that interferes with gene activation . Host genetic polymorphism related to immune response has been shown to be correlated with altered gene expression and susceptibility to developing DHF, such as the TNF-308 allele, associated with high levels of TNFa, has been correlated with increased risk of developing the most severe form disease (Fernandez-Mestre, Gendzekhadze et al. 2004; Soundravally and Hoti 2007). An association has recently been reported between the wild genotype ΆΆ MBL2, high levels of MBL and high risk of developing thrombocytopenia associated with dengue virus infection (Acioli-Santos, Segat et al. 2008). On the other hand, polymorphism in the CD209 promoter (Sakuntabhai, Turbpaiboon et al. 2005), was associated with reduced expression of DC-SIGN and, possibly, reduced susceptibility of dendritic cells to infection by the dengue virus. Therefore, the search for alteration in gene expression among different dengue clinical conditions using DNA microarrays can elucidate on a large scale the genetic factors and immunopathological mechanisms related to dengue severity.
Usando essa tecnologia, o perfil de expressão gênica foi caracterizado em pessoas que desenvolveram FHD em duas diferentes coortes:Using this technology, the gene expression profile was characterized in people who developed DHF in two different cohorts:
Simmons at al. (2007) mostraram uma assinatura molecular em células mononucleares de sangue periférico (PBMC) representando as fases aguda convalescente de pacientes que desenvolveram síndrome de choque de dengue (SCD). Neste trabalho eles relataram que transcritos gênicos para 24 genes estimulados por interferon estavam menos abundante em adultos (6 pacientes) com SCD do que e 8 pacientes com pacientes FHD que não desenvolveram choque, enquanto aqueles genes envolvidos em apoptose estavam expressos em maior quantidade Recentemente Ubol et al (2008) numa coorte de crianças Tailandesas também observaram redução ιSimmons at al. (2007) showed a molecular signature in peripheral blood mononuclear cells (PBMC) representing the acute convalescent phases of patients who developed dengue shock syndrome (SCD). In this work they reported that gene transcripts for 24 interferon-stimulated genes were less abundant in adults (6 patients) with SCD than and 8 patients with DHF patients who did not develop shock, whereas those genes involved in apoptosis were expressed in greater numbers Recently Ubol et al (2008) in a cohort of Thai children also observed a reduction ι
na expressão de genes da imunidade inata e aumento da expressão de genes envolvidos em apoptose com gravidade da infecção pelo vírus da dengue (Ubol, Masrinoul et al. 2008).in the expression of innate immunity genes and increased expression of genes involved in apoptosis with severity of dengue virus infection (Ubol, Masrinoul et al. 2008).
Durante a fase aguda da infecção, pacientes afetados com a forma benigna (FD) e maligna (FHD) da doença desenvolvem o mesmo quadro clínico. No entanto, durante o período de defervescência (4 a 7 dias do início dos sintomas) é acompanhado pelos distúrbios circulatórios, cuja magnitude é diretamente proporcional a gravidade da doença (WHO 1999). Com isso, os eventos que precedem a defervescência são determinantes para resposta clínica do paciente.During the acute phase of the infection, patients affected with the benign (FD) and malignant (FHD) forms of the disease develop the same clinical picture. However, during the defervescence period (4 to 7 days from the onset of symptoms) it is accompanied by circulatory disorders, the magnitude of which is directly proportional to the severity of the disease (WHO 1999). Thus, the events that precede defervescence are decisive for the patient's clinical response.
A presente invenção fornece o uso da expressão diferencial de um grupo de genes como ferramenta prognostica para predizer resposta clínica de pacientes infectados com dengue baseado nos dados de expressão gênica obtida, antes de começarem os sintomas circulatórios, usando microarranjos de oligonucleotidios. Amostras de sangue heparinizado (também pode ser utilizado citrato de sódio ou EDTA como anticoagulante) coletados de pacientes (Tabela 1), cuja infecção pelo vírus da dengue foi confirmada por sorologia para IgM assim como isolamento viral ou detecção de RNA viral através de RT-PCR; foram usados. Isolamento de PBMC usando gradiente de densidade pode ser usado para minimizar o ruído causado pelos granulócitos. Consequentemente, moderada a pequena mudanças na expressão gênica entre as diferentes manifestações clínicas de dengue pode ser prontamente detectada. Uma vez obtidas as amostras contendo as células, o RNA mensageiro ou total pode ser extraído e amplificado para avaliação da expressão gênica. O RNA amplificado é então marcado para que este possa ser hibridizado num microarranjo de DNA, que por sua vez, é escaneado e os dados obtidos são processados para a obtenção dos dados de perfil de expressão gênica.The present invention provides the use of the differential expression of a group of genes as a prognostic tool to predict clinical response of patients infected with dengue based on the gene expression data obtained, before the circulatory symptoms begin, using oligonucleotide microarrays. Heparinized blood samples (sodium citrate or EDTA can also be used as an anticoagulant) collected from patients (Table 1), whose infection with the dengue virus was confirmed by serology for IgM as well as viral isolation or detection of viral RNA using RT- PCR; was used. Isolation of PBMC using density gradient can be used to minimize noise caused by granulocytes. Consequently, moderate to small changes in gene expression between the different clinical manifestations of dengue can be readily detected. Once the samples containing the cells are obtained, the messenger or total RNA can be extracted and amplified to evaluate gene expression. The amplified RNA is then marked so that it can be hybridized in a microarray of DNA, which in turn is scanned and the obtained data are processed to obtain the gene expression profile data.
A qualidade dos dados do microarranjo de DNA é avaliada usando vários critérios:The quality of the DNA microarray data is assessed using several criteria:
inspeção visual, medida da relação ruido/eficiência, genes controles embutidos (spiked in) de amplificação (dap, thr, phe, lys) e hibridização (bioB, bioC, bioD, cre), expressão de genes constitutivos (GAPDH - gliceraldeido-visual inspection, measurement of the noise / efficiency ratio, built-in control genes (spiked in) for amplification (dap, thr, phe, lys) and hybridization (bioB, bioC, bioD, cre), expression of constitutive genes (GAPDH - glyceraldehyde-
3-fosfatase desidrogenase humano- e beta actina), e gráficos de degradação de RNA.Human 3-phosphatase dehydrogenase- and beta actin), and graphs of RNA degradation.
Inspeção visual baseada em arquivos de alta definição DAT não deve revelar sinais de arranhões ou manchas e as sondas oligos B2 devem ser visíveis (perfil de tabuleiro de xadrez bem como o nome do arranjo).Visual inspection based on high definition DAT files should not reveal signs of scratches or stains and the oligos B2 probes must be visible (chessboard profile as well as the name of the arrangement).
Medida da relação ruído/eficiência é feita pelo programa MAS 5.0. Fator Q de ruído, background, fator de escalonamento e percentagem de sondas presentes devem ser similar entre os microarranjos.The noise / efficiency ratio is measured using the MAS 5.0 program. Noise Q factor, background, scaling factor and percentage of probes present should be similar between microarrays.
A seleção dos genes preditores de resposta clínica de pacientes infectados com vírus da dengue, bem como aqueles característicos de infecção pelo vírus da dengue independente da manifestação clínica [comparação entre casos de dengue (FD + FHD) e grupo não dengue ou ND, cuja etiologia da doença febril foi desconhecida mas que foi descartada a possibilidade de ser pelo vírus da dengue], foi baseado em 26 microarranjos de oligonucleotidios distribuídos como se segue:The selection of genes that predict the clinical response of patients infected with dengue virus, as well as those characteristic of dengue virus infection regardless of clinical manifestation [comparison between dengue cases (FD + FHD) and non-dengue group or ND, whose etiology of febrile disease was unknown but the possibility of being due to the dengue virus was ruled out], it was based on 26 microarrays of oligonucleotides distributed as follows:
oriundos de pacientes com FD, 10 de pacientes FHD e 8 de pacientes ND. Esses microarranjos foram analisados através do programa Affymetrix MAS 5.0 (Hubbell, Liu et al. 2002) para normatizar os dados e produzir sinal e detectar as sondas presentes dentre os 54.675 transcritos gênicos em cada microarranjo. Desses, 12.299 transcritos foram considerados presentes (p<0.04) em todas os microarranjos, enquanto 20.365 transcritos foram considerados ausentes em qualquer dos microarranjos.from patients with FD, 10 from FHD patients and 8 from ND patients. These microarrays were analyzed using the Affymetrix MAS 5.0 program (Hubbell, Liu et al. 2002) to standardize the data and produce signals and detect the probes present among the 54,675 gene transcripts in each microarray. Of these, 12,299 transcripts were considered present (p <0.04) in all microarrays, while 20,365 transcripts were considered absent in any of the microarrays.
Para manter apenas os genes mais promissores para futuras análises, foram empregados dois filtros inespecificos: (i) filtro de detecção para eliminar genes não expressos, o que manteve apenas os genes considerados presentes em pelo menos 24 dos 26 microarranjos, resultando num total de 15.848 genes. Desta forma, foram tolerados 3.549 genes (15.848 - 12.299 = 3.549) que foram considerados ausentes em um ou dois microarranjos; (ii) filtro de variância para eliminar genes de expressão constitutiva, o que manteve os maiores 1/8 dos 15.848 genes previamente citados, resultando em 1981 genes com potencial prognóstico (Tabela 7). Esses genes foram confirmados como potenciais prognósticos quando foram realizados agrupamento hierárquico e escalonamento multidimensional em 2D e 3-D (Figure 3) , revelando a formação de dois grandes grupos, um grupo contendo amostras ND e metade das amostras FD; e outro grupo contendo pacientes FHD, duas amostras ND e a outra metade dos pacientes FD. A medida de dissimilaridade usada foi 1 - r, onde r é correlação de Pearson dos valores transformados em log. Os microrranjos foram coloridos de acordo com a classe diagnostica. Nota-se que as amostras FHD constituem um grupo mais coeso do que o grupo ND, representado por pacientes com doenças febris de etiologia desconhecida. Enquanto as amostras FD podem ser divididas em dois grupos, um similar e outro diferente das amostras FHD, este último estando mais próximo das amostras ND. O pequeno valor de estresse (13.52% no Gráfico 2-D e 7.32% no Gráfico 3-D), particularmente no Gráfico 3-D significa que a estrutura que os dados representam é intrinsecamente de baixa dimensão, o que indica que um pequeno número de assinaturas gênicas pode representar o conteúdo discriminatório dos dados.In order to keep only the most promising genes for future analyzes, two nonspecific filters were used: (i) detection filter to eliminate unexpressed genes, which kept only the genes considered to be present in at least 24 of the 26 microarrays, resulting in a total of 15,848 genes. Thus, 3,549 genes (15,848 - 12,299 = 3,549) were tolerated, which were considered absent in one or two microarrays; (ii) variance filter to eliminate genes of constitutive expression, which kept the largest 1/8 of the 15,848 previously cited genes, resulting in 1981 genes with prognostic potential (Table 7). These genes were confirmed as potential prognoses when hierarchical grouping and multidimensional scaling were performed in 2D and 3-D (Figure 3), revealing the formation of two large groups, one group containing ND samples and half of the FD samples; and another group containing DHF patients, two ND samples and the other half of DH patients. The measure of dissimilarity used was 1 - r, where r is Pearson's correlation of the values transformed into log. The microorganisms were colored according to the diagnostic class. It is noted that FHD samples constitute a more cohesive group than the ND group, represented by patients with febrile diseases of unknown etiology. While the FD samples can be divided into two groups, a similar and a different one from the FHD samples, the latter being closer to the ND samples. The small amount of stress (13.52% in Graph 2-D and 7.32% in Graph 3-D), particularly in Graph 3-D means that the structure that the data represents is intrinsically small, which indicates that a small number of gene signatures can represent the discriminatory content of the data.
Em seguida foi realizado um teste estatístico entre as médias (Welch two-sample t-tests) para achar os genes que foram diferencialmente expressos entre os diferentes grupos analisados. Duas comparações foram consideradas: FD verso FHD e Dengue (FD+FHD) verso ND. Gráficos de vulcão na Figura 4 mostram que os valores p foram bem correlacionados com magnitude de diferença de expressão (fold change) em ambas as comparações. A lista de genes com maiores fold-change mostrados nos gráficos vulcão são mostrados nas Tabelas 2 e 3Then, a statistical test was performed between the means (Welch two-sample t-tests) to find the genes that were differentially expressed between the different groups analyzed. Two comparisons were considered: FD versus FHD and Dengue (FD + FHD) versus ND. Volcano graphs in Figure 4 show that the p values were well correlated with the magnitude of the difference in expression (fold change) in both comparisons. The list of genes with the greatest fold-change shown in the volcano charts are shown in Tables 2 and 3
A Figura 5 mostra o mapa de expressão para os 40 mais significativos (menores valores p) genes que discriminam os grupos FD de FHD de acordo com o critério do teste Welch t, assim como o agrupamento hierárquico e gráficos MDS para os mesmos 40 genes.Figure 5 shows the expression map for the 40 most significant (lowest p-values) genes that discriminate FD FHD groups according to the Welch t test criteria, as well as the hierarchical grouping and MDS graphs for the same 40 genes.
Entre os 200 mais significativos genes diferencialmente expressos entre FD e FHD de acordo com o Welch two-sample ttests foi comparado com 200 genes com maiores fold-change da média de expressão dos níveis de RNAm, há 7 3 genes em comum (Tabela 6) , o que representa os melhores genes mais significativos e com maior diferença na magnitude de expressão (fold-change) entre FD e FHD.Among the 200 most significant genes differentially expressed between FD and FHD according to Welch two-sample ttests was compared with 200 genes with greater fold-change in the average expression of mRNA levels, there are 7 3 genes in common (Table 6) , which represents the best most significant genes and with the greatest difference in the magnitude of expression (fold-change) between FD and FHD.
Dentre os genes diferencialmente expressos entre FD e FHD, 19 fazem parte da categoria de resposta imune, incluindo HLA-ΏΡαβ genes, complement factor D, CX3CR, MyD88, TNFSF17 (BCMA), TNFSF13 (APRIL). Sete genes foram incluídos no grupo de resposta a defesa, entre eles temos o gene de Resistência a mixovírus (Mx), 2’, 5'-oligoadenilato sintetase (OAS1 and OAS2) e fatores estimulados por IFN. Estes foram expressos em menor magnitude em pessoas que depois desenvolveram FHD. Este genes tem sido implicados em resposta imune inata, confirmando que esse braço da resposta imune pode ser crucial para a resposta clínica de pacientes infectados com o vírus da dengue. Alem disso, 6 genes (PDCD4, PACAP, Tumor protein D52, MAGED1, proapoptotic caspase adaptor protein and TNF ligand super family) associados com apoptose estão expressos em maior quantidade em pacientes FHD. Além disso, CD53, uma tetraspanina produzida por monócitos e linfócitos B e previne essas células de sofrerem apoptose (Yunta and Lazo 2003) estava expressa em menor quantidade no grupo FHD, reforçando a premissa de que aumento de células que sofre apoptose está associado com desenvolvimento da forma mais severa da doença.Among the genes differentially expressed between FD and FHD, 19 are part of the immune response category, including HLA-ΏΡαβ genes, complement factor D, CX3CR, MyD88, TNFSF17 (BCMA), TNFSF13 (APRIL). Seven genes were included in the defense response group, among them we have the myxovirus resistance gene (Mx), 2 ', 5'-oligoadenylate synthase (OAS1 and OAS2) and factors stimulated by IFN. These were expressed to a lesser extent in people who later developed DHF. These genes have been implicated in an innate immune response, confirming that this arm of the immune response may be crucial to the clinical response of patients infected with the dengue virus. In addition, 6 genes (PDCD4, PACAP, Tumor protein D52, MAGED1, proapoptotic caspase adapter protein and TNF ligand super family) associated with apoptosis are expressed in greater numbers in FHD patients. In addition, CD53, a tetraspanin produced by monocytes and B lymphocytes and prevents these cells from undergoing apoptosis (Yunta and Lazo 2003) was expressed to a lesser extent in the FHD group, reinforcing the premise that an increase in apoptosis-associated cells is associated with development the most severe form of the disease.
Comparando com o estudo conduzido por Simmons et al (2007) (Simmons, Popper et al. 2007), existe uma consistência nos genes propostos como sendo prognósticos para desenvolvimento de FHD. Neste estudo, alguns genes estimulados por IFN, cuja expressão estava reduzida em pacientes desenvolvendo SCD, tais como as MX, IFIT, and OAS, bem como níveis elevados de pro-apoptotíc caspase adaptor protein eComparing with the study conducted by Simmons et al (2007) (Simmons, Popper et al. 2007), there is a consistency in the genes proposed as being prognostic for the development of DHF. In this study, some genes stimulated by IFN, whose expression was reduced in patients developing SCD, such as MX, IFIT, and OAS, as well as high levels of pro-apoptotic caspase adapter protein and
PDCD5 (programmed cell death 5) fazem parte da nossa lista de genes prognósticos.PDCD5 (programmed cell death 5) are part of our list of prognostic genes.
Desta forma, com base nos 1981 genes identificados foram selecionados grupos de genes marcadores de FHD para serem utilizados em ensaios mais simples, tais como PCR quantitativa. Para isso, foi realizada uma seleção exaustiva com todas as possíveis combinações de genes isolados ou combinados em forma de dupla ou trio, através análise discriminante linear como método de classificação, implementado pela estimativa direta das médias das amostras e matrizes de covariância para cada classe diagnostica (Braga-Neto 2005); e precisão de classificação estimada pelo método de resubstituição potencializada (bolstead resubstitution, Braga-Neto 2004), que é ideal para seleção de grupo de genes numa situação com número menor de amostra (Sima, Attoor et al. 2005; Sima, Braga-Neto et al. 2005).Thus, based on the 1981 identified genes, groups of FHD marker genes were selected to be used in simpler assays, such as quantitative PCR. For this, an exhaustive selection was carried out with all possible combinations of genes isolated or combined in the form of a pair or trio, through linear discriminant analysis as a classification method, implemented by direct estimation of sample means and covariance matrices for each diagnostic class. (Braga-Neto 2005); and classification accuracy estimated by the potentiated resubstitution method (bolstead resubstitution, Braga-Neto 2004), which is ideal for selecting a group of genes in a situation with a smaller sample size (Sima, Attoor et al. 2005; Sima, Braga-Neto et al. 2005).
A Tabela 5 mostra os melhores genes na forma isolada (40) ou combinada [dupla (40) ou trio (100)], ranqueados pelo erro estimado. Há 37 únicos genes entre os melhores 40 pares, enquanto há 86 únicos genes em os melhores 100 trios. A lista de trios é dominada pelos genes PSMB9, MT2A e LOC400368. A média do erro estimado para os melhores classificadores contendo 1 gene (40) = 0.1639 ± 0.0286, 2 genes (40) = 0.0686 ± 0.0096, 3 genes (100) = 0.0395 ± 0.0040, o que indica que a classificação usando pares de genes é mais precisa que 1 gene, enquanto a classificação utilizando 3 genes é mais precisa do que 2 genes (a margem de erro acima se refere a um intervalo de confidência de 95%) . O método de seleção acima descrito com 2 ou 3 genes tem um potencial de selecionar genes que não são possíveis de serem encontrados usando métodos univariados, tais como t-test. Isto pode ser visto na lista com os melhores duplas de classificadores. Por exemplo, o gene HLA-F (cuja expressão é reduzida in FHD em relação a FD) A Figura 6 mostra o gráfico contendo um dos genes classificadores baseado na dupla de genes PSMB9 e MT2A. A probabilidade de erro em futuros dados para este classificador é de 5.38%. Neste caso, reduzida expressão de ambos os genes é característica de FHD, enquanto aumento de expressão é característica de FD. Para confirmar a potencialidade desses genes como preditores de gravidade de dengue, selecionamos alguns (PSMB9, MT2A, HLA-F and C3aRl) para desenvolver ensaios de RT-PCR quantitativo com amostras FD e FHD. Os genes foram amplificados e detectados usando o ensaio de expressão gênica TaqMan® com iniciadores (primers) e sondas comercialmente disponíveis (Applied Biosystems). O RNA foi extraído com auxilio do kit RNeasy (Qiagen) . O RNA total foi reversamente transcrito usando o sistema de síntese da primeira fita SuperScript III para PCR quantitativo usando iniciadores aleatórios (random primers) e a PCR quantitativa foi realizada no ABI PRISM 7500 (Applied Biosystems). Beta actina foi usado como controle endógeno e todos os dados foram normalizados baseados neste gene constitutivo. As amostras usadas neste ensaio são descritas na Tabela 1 (amostras de pacientes ND, bem como os pacientes FHD 105 e 112 não foram usados). Os resultados de RT-PCR quantitativa foram comparáveis com aqueles obtidos nos ensaios de microarranjos (Figura 7). Além disso, usando um grupo de amostras independentes daquelas amostras usadas nos ensaios de microarranjos, os níveis de acima também foram confirmados resultados do ensaio de PCR expressão dos genes citados (Figura 7). Desta forma, os quantitativa confirmaram a expressão dos genes selecionados em amostras coletadas na primeira visita médica de um paciente infectado com vírus da dengue, podendo predizer se uma pessoa infectada pelo vírus da dengue pode desenvolver ou não FHD. Portanto, o objeto desta invenção representa um meio útil de guiar o manejo clínico de pacientes com dengue.Table 5 shows the best genes in isolated (40) or combined [double (40) or trio (100)], ranked by the estimated error. There are 37 unique genes among the best 40 pairs, while there are 86 unique genes in the best 100 trios. The list of trios is dominated by the PSMB9, MT2A and LOC400368 genes. The average estimated error for the best classifiers containing 1 gene (40) = 0.1639 ± 0.0286, 2 genes (40) = 0.0686 ± 0.0096, 3 genes (100) = 0.0395 ± 0.0040, which indicates that the classification using pairs of genes it is more accurate than 1 gene, while classification using 3 genes is more accurate than 2 genes (the margin of error above refers to a 95% confidence interval). The selection method described above with 2 or 3 genes has the potential to select genes that are not possible to be found using univariate methods, such as t-test. This can be seen in the list of the best classifier pairs. For example, the HLA-F gene (whose expression is reduced in FHD compared to FD) Figure 6 shows the graph containing one of the classifier genes based on the PSMB9 and MT2A gene pair. The probability of error in future data for this classifier is 5.38%. In this case, reduced expression of both genes is characteristic of FHD, while increased expression is characteristic of FD. To confirm the potential of these genes as predictors of dengue severity, we selected some (PSMB9, MT2A, HLA-F and C3aRl) to develop quantitative RT-PCR assays with FD and FHD samples. The genes were amplified and detected using the TaqMan® gene expression assay with commercially available primers and probes (Applied Biosystems). The RNA was extracted with the aid of the RNeasy kit (Qiagen). The total RNA was reverse transcribed using the first SuperScript III strand synthesis system for quantitative PCR using random primers and quantitative PCR was performed on the ABI PRISM 7500 (Applied Biosystems). Beta actin was used as an endogenous control and all data were normalized based on this constitutive gene. The samples used in this assay are described in Table 1 (samples from ND patients, as well as patients FHD 105 and 112 were not used). The results of quantitative RT-PCR were comparable to those obtained in the microarray assays (Figure 7). In addition, using a group of samples independent of those samples used in the microarray assays, the above levels were also confirmed results of the PCR assay expression of the mentioned genes (Figure 7). In this way, the quantitative ones confirmed the expression of the selected genes in samples collected in the first medical visit of a patient infected with dengue virus, being able to predict whether a person infected with the dengue virus may or may not develop DHF. Therefore, the object of this invention represents a useful means of guiding the clinical management of patients with dengue.
Métodos de escolha para estabelecer níveis de expressão gênica para predição de resposta clínica de pacientes com dengue incluem microarranjos de DNA, RT-PCR, northern blot, RT-PCR competitiva, RT-PCR em tempo real, diferential display RT-PCR. Enquanto é possível conduzir essas técnicas usando reações de PCR individuais, é melhor amplificar o DNA complementar (cDNA) e analisá-lo via PCR quantitativa e então normalizar os resultados usando a expressão de algum gene constitutivo. Em seguida, as análises poderão ser feitas usando quantificação tanto absoluta quanto relativa para que o perfil de expressão gênica possa ser determinado.Methods of choice for establishing levels of gene expression for predicting the clinical response of patients with dengue include DNA microarrays, RT-PCR, northern blot, competitive RT-PCR, real-time RT-PCR, differential display RT-PCR. While it is possible to conduct these techniques using individual PCR reactions, it is best to amplify the complementary DNA (cDNA) and analyze it via quantitative PCR and then normalize the results using the expression of some constitutive gene. Then, the analyzes can be done using both absolute and relative quantification so that the gene expression profile can be determined.
Níveis de proteínas codificadas pelos genes preditivos de gravidade da dengue, quantificados de qualquer fluido corpóreo (sangue, plasma, soro, exudados) podem ser usadas para prognóstico de gravidade da dengue. No entanto, amostras de plasma são preferidas. Para estes tipos de amostras, qualquer ensaio imunológico (ELISA, imunofluorescência, western blot, dot blot etc) pode ser empregado. Além do mais, níveis de proteínas podem ser indiretamente avaliados através da análise da frequência de células (PBMC, por exemplo) expressando uma dada proteína em qualquer compartimento de células por citometria de fluxo.Levels of proteins encoded by dengue severity predictive genes, quantified from any body fluid (blood, plasma, serum, exudates) can be used for prognosis of dengue severity. However, plasma samples are preferred. For these types of samples, any immunological assay (ELISA, immunofluorescence, western blot, dot blot etc.) can be used. Furthermore, protein levels can be indirectly assessed by analyzing cell frequency (PBMC, for example) expressing a given protein in any cell compartment by flow cytometry.
O uso de qualquer dos métodos acima mencionados e outros relacionados constitui uma fonte para desenvolvimento de kits preditores de gravidade da dengue durante a fase aguda da infecção e antes que o extravasamento plasmático ocorra em pacientes FHD.The use of any of the aforementioned and related methods is a source for the development of kits for predicting dengue severity during the acute phase of infection and before plasma leakage occurs in DHF patients.
A invenção é ilustrada pelo seguintes exemplos a seguir os quais não devem ser considerados como limitantes do escopo de proteção.The invention is illustrated by the following examples which are not to be considered as limiting the scope of protection.
EXEMPLOSEXAMPLES
Os genes analisados de acordo com esta invenção são tipicamente relacionados a completa sequência de ácidos nucléicos que codificam para produção de uma proteína ou peptídeo. No entanto, a identificação da sequência completa não é necessária do ponto de vista analítico. Isto é, porções da sequência ou ESTs podem ser selecionadas de acordo com os princípios bem conhecidos para as quais as sondas podem ser desenhadas para avaliar a expressão gênica para o correspondente gene.The genes analyzed according to this invention are typically related to the complete sequence of nucleic acids that code for the production of a protein or peptide. However, the identification of the complete sequence is not analytically necessary. That is, portions of the sequence or ESTs can be selected according to the well-known principles for which the probes can be designed to assess gene expression for the corresponding gene.
Exemplo 1 - Desenho da coorte de dengue e estratégia para estudos de genômica funcionalExample 1 - Design of the dengue cohort and strategy for functional genomics studies
Uma coorte de casos febris de casos suspeitos de infecção pelo vírus da dengue atendidos em 3 hospitais da cidade de Recife, Pernambuco, Brasil, foi estabelecido e descrito (Cordeiro, Schatzmayr et al. 2007; Cordeiro, Silva et al. 2007). Brevemente, apenas a completa explicação dos objetivos do estudo, a cada participante desta coorte (ou responsável) foi solicitado a assinatura do termo de consentimento e foi pedido uma doação sequencial de sangue dentro de um período de 30 dias apos o inicio dos sintomas. Soro, plasma e PBMC foram separados e criopreservados. 0 diagnóstico de dengue foi realizado através de isolamento viral em células C6/36 (Igarashi 1978) e RT-PCR (Lanciotti, Calisher et al. 1992) nas amostras coletadas no dia da admissão (primeira amostra) assim como através de sorologia para identificação de IgM (Bio-Manguinhos, Fundação Oswaldo Cruz, Brasil ou PanBio, Pty., Ltd., Brisbane, Austrália) e IgG (PanBio, Pty., Ltd., Brisbane, Austrália) anti-dengue na primeira e subseguentes amostras. 0 tipo de infecção foi caracterizado baseado na cinética de produção de IgM/IgG e títulos de anticorpos em ensaio de inibição de hemaglutinação (HI) (Clarke and Casais 1958).A cohort of feverish cases of suspected dengue virus infection treated at 3 hospitals in the city of Recife, Pernambuco, Brazil, was established and described (Cordeiro, Schatzmayr et al. 2007; Cordeiro, Silva et al. 2007). Briefly, only a complete explanation of the study objectives, each participant of this cohort (or guardian) was asked to sign the consent form and a sequential blood donation was requested within a period of 30 days after the onset of symptoms. Serum, plasma and PBMC were separated and cryopreserved. The diagnosis of dengue was made through viral isolation in C6 / 36 cells (Igarashi 1978) and RT-PCR (Lanciotti, Calisher et al. 1992) in the samples collected on the day of admission (first sample) as well as through serology for identification IgM (Bio-Manguinhos, Oswaldo Cruz Foundation, Brazil or PanBio, Pty., Ltd., Brisbane, Australia) and IgG (PanBio, Pty., Ltd., Brisbane, Australia) anti-dengue in the first and subsequent samples. The type of infection was characterized based on the kinetics of IgM / IgG production and antibody titers in hemagglutination inhibition (HI) assay (Clarke and Casais 1958).
Os casos de dengue (confirmados por sorologia, RT-PCR ou isolamento viral) foram clinicamente classificados de acordo com o critério da Organização Mundial de Saúde em duas classes: febre de dengue (FD ou dengue clássica) e febre hemorrágica do dengue (FHD) (OPAS 1995). Os casos de FD foram caracterizados por febre (39°C to 40°C) durando até 7 dias acompanhado por pelo menos 2 dos sintomas, tais com odor de cabeça, dor retrorbital, mialgia, artralgia e rash. Os casos de FHD foram definidos com a mesma sintomatologia encontrada em FD, mas com evidência de hemorragia, trombocitopenia (plaquetas <1000.000/mm3) e extravasamento plasmático seguindo a defervescência.Dengue cases (confirmed by serology, RT-PCR or viral isolation) were clinically classified according to the criteria of the World Health Organization into two classes: dengue fever (FD or classic dengue) and dengue hemorrhagic fever (DHF) (PAHO 1995). FD cases were characterized by fever (39 ° C to 40 ° C) lasting up to 7 days accompanied by at least 2 of the symptoms, such as head odor, retrorbital pain, myalgia, arthralgia and rash. DHF cases were defined with the same symptoms found in DH, but with evidence of hemorrhage, thrombocytopenia (platelets <1000,000 / mm3) and plasma leakage following defervescence.
Este estudo foi revisado e aprovado pelo comitê de ética do Ministério da Saúde Brasileiro CONEP : 4909; Processo n° 25000.119007/2002-03; CEP: 68/02. Além disso, o comitê de revisão institucional da Universidade Johns Hopkins (EUA) também revisou e aprovou este estudo como protocolo JHM-IRB-3:This study was reviewed and approved by the ethics committee of the Brazilian Ministry of Health CONEP: 4909; Process No. 25000.119007 / 2002-03; CEP: 68/02. In addition, the institutional review committee at Johns Hopkins University (USA) also reviewed and approved this study as a JHM-IRB-3 protocol:
03-08-27-01.03-08-27-01.
Os estudos de genômica funcional foram realizados com amostras de PBMC coletadas no momento da primeira visita médica. Amostras provenientes de 18 casos confirmados de dengue (RT-PCR, isolamento viral e/ou IgM positivos), genótipo III, e 8 amostras controles provenientes de casos febris que foram negativos para dengue em todos os testes realizados em 3 ou mais amostras (aqui chamados de não dengue ou ND) foram usados nessa avaliação. As amostras foram divididas em três grupos: FD, FHD e ND. As amostras referentes a esses três grupos foram selecionadas para evitar diferença significante em relação a idade, gênero, histórico de infecção pelo virus da dengue e dias de sintomas. Nenhum dos pacientes apresentaram sintomas de FHD no momento que as amostras usadas nessa avaliação foram coletadas. No momento da coleta das amostras, os pacientes relataram que tiveram sintomas por menos de 8 dias (media de 5.3 dias). Entre os casos confirmados de dengue, 8 foram caracterizados como FD e 10 foram classificados como FHD (Tabela 1) . Em negrito na Tabela 1 estão indicadas as amostras usadas exclusivamente nos ensaios de qPCR. FD: febre do dengue; FHD: febre hemorrágica do dengue; ND: Non-Dengue; M: macho; F: fêmea; Pos: positivo; Neg: negativo; -: sem informação.Functional genomics studies were performed with PBMC samples collected at the time of the first medical visit. Samples from 18 confirmed dengue cases (RT-PCR, viral isolation and / or IgM positive), genotype III, and 8 control samples from febrile cases that were negative for dengue in all tests performed on 3 or more samples (here called non-dengue or ND) were used in this assessment. The samples were divided into three groups: FD, FHD and ND. The samples for these three groups were selected to avoid a significant difference in relation to age, gender, history of dengue virus infection and symptom days. None of the patients had symptoms of DHF at the time the samples used in this evaluation were collected. At the time of sample collection, patients reported having symptoms for less than 8 days (average of 5.3 days). Among confirmed dengue cases, 8 were characterized as FD and 10 were classified as DHF (Table 1). Bold in Table 1 are the samples used exclusively in the qPCR assays. DF: dengue fever; DHF: dengue hemorrhagic fever; ND: Non-Dengue; M: male; F: female; Pos: positive; Neg: negative; -: no information.
Exemplo 2 - Processamento das amostras para hibridização nos chips gênicosExample 2 - Processing of samples for hybridization in gene chips
Amostras de sangue coletados dos pacientes cadastrados nesta avaliação foram coletadas em tubos vacutainers heparinizados (BD Vacutainer) e dentro 2 horas da coleta, as amostras PBMC foram separadas por gradiente de densidade usando Ficoll-Paque (Amersham Biosciences) e criopreservadas em 10% (v/v) de dimetil sulfoxide (DMSO; Sigma-Aldrich) em soro fetal bovino inativado (FBS; Hyclone). Quatro milhões de células foram descongelados e imediatamente lisadas com Trizol (Invitrogen) para extração de RNA total com clorofórmio e precipitação com álcool isopropilico de acordo com as instruções do fabricante [a expressão usando amostras 10 frescas ou congeladas foram comparadas e se mostraram ser similares, razão pela qual células congeladas foram escolhidas para estudos de genômica funcional (dados não mostrados)] .Blood samples collected from patients enrolled in this evaluation were collected in heparinized vacutainer tubes (BD Vacutainer) and within 2 hours of collection, PBMC samples were separated by density gradient using Ficoll-Paque (Amersham Biosciences) and cryopreserved at 10% (v / v) dimethyl sulfoxide (DMSO; Sigma-Aldrich) in inactivated fetal bovine serum (FBS; Hyclone). Four million cells were thawed and immediately lysed with Trizol (Invitrogen) to extract total RNA with chloroform and precipitation with isopropyl alcohol according to the manufacturer's instructions [the expression using fresh or frozen samples 10 was compared and shown to be similar, which is why frozen cells were chosen for functional genomics studies (data not shown)].
O RNA total foi, então, purificado usando o kit RNeasy 15 MinElute Cleanup (Qiagen) de acordo com o protocolo do fabricante e quantificado por espectrofotometria a 260nm e 280nm (espectro ultravioleta). RNA total foi usado para a síntese de RNA complementar (cRNA) através do kit de marcação do alvo em dois ciclos (Affymetrix). Brevemente, RNA isolado 20 de PBMC foi marcado com biotina e hibridizado a microarranjos de oligonucleotideos (Affymetrix) usando um método de síntese de cDNA em dois ciclos. No primeiro ciclo, a primeira fita de cDNA foi preparada usando um iniciador T7-(dT) e a transcriptase reversa Superscript II (Invitrogen) a partir de 25 10-100ng de RNA celular. A síntese da segunda fita foi realizada usando DNA polimerase I de Escherichia coli e cDNA de dupla fita foi usado no ensaio de transcrição in vitro (IVT) para amplificação de cRNA usando o kit Megascript T7 (Ambion). O produto deste primeiro ciclo de reações foi usado para transcrição reversa de cDNA como descrito para o primeiro ciclo. Este cDNA foi usado para IVT para síntese de cRNA marcado com biotina, que foi fragmentado e enviado para o Microarray Core Facility na Universidade Johns Hopkins para hibridização do cRNA ao chip de DNA humano U133 Plus 2.0 (Affymetrix), marcação e escaneamento.The total RNA was then purified using the RNeasy 15 MinElute Cleanup kit (Qiagen) according to the manufacturer's protocol and quantified by spectrophotometry at 260nm and 280nm (ultraviolet spectrum). Total RNA was used for the synthesis of complementary RNA (cRNA) through the targeting kit in two cycles (Affymetrix). Briefly, RNA isolated from PBMC was labeled with biotin and hybridized to microarrays of oligonucleotides (Affymetrix) using a two-cycle cDNA synthesis method. In the first cycle, the first cDNA strand was prepared using a T7- (dT) primer and Superscript II reverse transcriptase (Invitrogen) from 10-100ng cellular RNA. The second strand synthesis was performed using Escherichia coli DNA polymerase I and double stranded cDNA was used in the in vitro transcription assay (IVT) for cRNA amplification using the Megascript T7 kit (Ambion). The product of this first reaction cycle was used for reverse cDNA transcription as described for the first cycle. This cDNA was used for IVT for the synthesis of biotin-labeled cRNA, which was fragmented and sent to the Microarray Core Facility at Johns Hopkins University to hybridize the cRNA to the U133 Plus 2.0 human DNA chip (Affymetrix), tagging and scanning.
Exemplo 3 - Controle de qualidade dos microarranjosExample 3 - Quality control of microarrays
A qualidade dos dados dos microarranjos foi avaliada usando os seguintes critérios: inspeção visual, medidas da relação ruído/eficiência, controles embutidos, expressão de genes constitutivos, e gráficos de degradação de RNA. Inspeção visual baseada em arquivos de alta resolução DAT não revelaram arranhões ou manchas, e as sondas B2-oligo (num formato de tabuleiro de xadrez e o nome do microarranjo) foram também visíveis. Medidas de ruído/eficiência foram feitas pelo programa Affymetrix MAS 5.0 que pode ser usado para avaliar a qualidade dos microarranjos (Figure 1). Fatores Q de ruído, background, fatores de escalonamento e percentagem de genes presentes foram similares em todas os microarranjos. Os valores médios de background foram abaixo de 100 para 20 dos 26 microarranjos; os fatores de escalonamento foram dentro da ordem de 3x para 2 5 dos 2 6 microarranjos; e a percentagem de genes presentes foi em torno de 40% ou mais para 25 dos 26 microarranjos. Nenhum dos 6 microarranjos que apresentaram alto background tiveram uma taxa de genes presentes significantemente abaixo de 40%. Todos as sondas 3' e as sondas da parte intermediária para todos os genes controles embutidos (dap, thr, phe, lys) estavam presentes em todos os microarranjos, assim como para o grupo de genes procarióticos usados para o controle da hibridização (bioB, bioC, bioD, cre) e genes constitutivosThe quality of the microarray data was assessed using the following criteria: visual inspection, measures of the noise / efficiency ratio, built-in controls, expression of constitutive genes, and graphs of RNA degradation. Visual inspection based on high-resolution DAT files revealed no scratches or stains, and the B2-oligo probes (in a chessboard format and the name of the microarray) were also visible. Noise / efficiency measurements were made using the Affymetrix MAS 5.0 program, which can be used to assess the quality of the microarrays (Figure 1). Noise Q factors, background, scaling factors and percentage of genes present were similar in all microarrays. The average background values were below 100 for 20 of the 26 micro arrays; the scaling factors were within the order of 3x for 2 5 of the 2 6 micro arrays; and the percentage of genes present was around 40% or more for 25 of the 26 microarrays. None of the 6 microarrays that had a high background had a gene rate present significantly below 40%. All 3 'probes and intermediate probes for all embedded control genes (dap, thr, phe, lys) were present in all microarrays, as well as for the group of prokaryotic genes used to control hybridization (bioB, bioC, bioD, cre) and constitutive genes
GAPDH (gliceraldeido-3-fosfatase desidrogenase humano) e beta-actina.Além do mais, o gráfico de degradação de RNA mostrando a intensidade média das sondas na mesma posição numérica em todos os grupos de sondas (para todos os genes) demonstra uma consistente tendência de aumento na intensidade de sinal a partir do final 5' para o final 3' , o que é esperado devido a decréscimo na eficiência na síntese de cDNA (Figura 2).GAPDH (human glyceraldehyde-3-phosphatase dehydrogenase) and beta-actin.In addition, the RNA degradation graph showing the average intensity of the probes in the same numerical position in all probe groups (for all genes) demonstrates a consistent tendency to increase in signal intensity from the 5 'end to the 3' end, which is expected due to the decrease in efficiency in cDNA synthesis (Figure 2).
Exemplo 5 - Validação dos dados de Microarranjo de DNA através de PCR em tempo real quantitativoExample 5 - Validation of DNA Microarray data through quantitative real-time PCR
Quatro genes diferencialmente expressos entre DF e FHD (MT2A, PSMB9, C3aRl e HLA-F) foram selecionados para quantificação por PCR em tempo real quantitativo (qPCR). Os genes foram amplificados e detectados usando ensaios de expressão gênica TaqMan® com iniciadores e sondas comercialmente disponíveis (Applied Biosystems). Extração deFour genes differentially expressed between DF and FHD (MT2A, PSMB9, C3aRl and HLA-F) were selected for quantification by quantitative real-time PCR (qPCR). The genes were amplified and detected using TaqMan® gene expression assays with commercially available primers and probes (Applied Biosystems). Extraction of
RNA foi realizada usando o kit RNease (Qiagen) de acordo com as instruções do fabricante. RNA total foi reversamente transcrito a cDNA usando o sistema de síntese de primeira fita SuperscriptRNA was performed using the RNease kit (Qiagen) according to the manufacturer's instructions. Total RNA was reverse transcribed to cDNA using the Superscript first-strand synthesis system
III (Invitrogen) para qPCR usando iniciadores aleatórios (radom primers) de acordo com a sugestão do fabricante.III (Invitrogen) for qPCR using random primers (radom primers) according to the manufacturer's suggestion.
qPCR foi realizado no aparelho ABIqPCR was performed on the ABI device
PRISM 7500 (Applied Biosystems). O gene para beta actina foi selecionado como um controle endógeno e todos os dados foram normalizados contra este. A reação foi realizada em triplicata e incluiu 2 μΐ de cDNA, iniciadores (20 μΜ cada) e 6.25 μΜ da sonda especifica ou comercialmente pré-desenhada mistura para ensaio de expressão gênica (Applied Biosystems), beta-actina humana (Applied Biosystems), mistura universal para PCR TaqMan (Applied Biosystems) e água adicionados para um volume final de 25 μΐ. Triplicatas de controles não templates (NTC) foram incluídos cada vez que qPCR foi realizada. Os ciclos de reações foram: após incubação de 2min a 50°C e 10 minutos a 95°C, as amostras passaram por 40 ciclos de 95°C por 15 segundos e 60°C por lmin. A linha de base e o threshold utilizados para a determinação do Cycle threshold foram ajustados manualmente através do programa Sequence Detection Software, versão 1.4 (Applied Biosystems). A eficiência de amplificação (E) da molécula-alvo foi calculada a partir da fórmula (E= 10Λ(-1/Slope) - 1) onde slope é inclinação da reta gerada pelos Cts obtidos de curva padrão, dado automaticamente pelo programa. Para os cálculos de quantificação relativa, foi utilizado o método baseado nos valores de Delta Ct [ABI PRISM® 7000 Sequence Detection System and AppliedBiosystems 7500 Real-Time PCR System - User Bulletin, Applied Biosystems] uma vez que os ensaios apresentam eficiência de amplificação de 100% ± 10% [Application Note 127AP05-02]. As amostras usadas nos ensaios de qPCR são descritas na Tabela 1 (amostras de pacientes ND e pacientes FHD número 105 e 112 não foram usados).PRISM 7500 (Applied Biosystems). The beta actin gene was selected as an endogenous control and all data were normalized against it. The reaction was carried out in triplicate and included 2 μΐ of cDNA, primers (20 μΜ each) and 6.25 μΜ of the specific or commercially pre-designed probe mixture for gene expression assay (Applied Biosystems), human beta-actin (Applied Biosystems), universal mix for TaqMan PCR (Applied Biosystems) and water added to a final volume of 25 μΐ. Triplicates of non-template controls (NTC) were included each time qPCR was performed. The reaction cycles were: after 2min incubation at 50 ° C and 10 minutes at 95 ° C, the samples went through 40 cycles of 95 ° C for 15 seconds and 60 ° C per lmin. The baseline and threshold used to determine the Cycle threshold were manually adjusted using the Sequence Detection Software, version 1.4 (Applied Biosystems). The amplification efficiency (E) of the target molecule was calculated from the formula (E = 10 Λ (-1 / Slope) - 1) where slope is the slope of the line generated by the Cts obtained from the standard curve, given automatically by the program. For the calculations of relative quantification, the method based on Delta Ct values was used [ABI PRISM® 7000 Sequence Detection System and AppliedBiosystems 7500 Real-Time PCR System - User Bulletin, Applied Biosystems] since the tests show efficiency of amplification of 100% ± 10% [Application Note 127AP05-02]. The samples used in the qPCR assays are described in Table 1 (samples from ND patients and FHD patients numbers 105 and 112 were not used).
Exemplo 6 - Análise EstatísticaExample 6 - Statistical Analysis
Controle de qualidade dos dados dos pacientes, análise estatística e gráficos foram realizados usando o programa Affymetrix MAS 5.0 (Hubbell, Liu et al. 2002) e o pacote estatístico R de acesso aberto, versão 2.5.0 (Ihaka 1996) e biblioteca adicional, em particular a biblioteca BioConductor, versão 1.16 (Gentleman, Carey et al. 2004). Dendogramas e gráficos MDS foram produzidos com as funções R hclust e isoMDS, respectivamente, enquanto os mapas de expressão (heatmaps) foram obtidos com as funções hset.emap e heatmap. Os valores p correspondentes a two-tailed Welch's two-sample t test foram obtidos com a função t-test. Análise de categoria funcional foi realizada com o programa EASE (Expression Analysis Systematic Explorer) no website DAVID Bioinformatic (http://david.abcc.ncifcrf.gov) (Dennis, Sherman et al. 2003). 0 método de classificação usou análise discriminante linear implementado pela direta estimativa da média das amostras e matrizes de covariância para cada classe diagnostica (Braga-Neto 2005). A precisão da classificação foi estimada pelo método de resubstituição potencializada (bolsted resubstitution, Braga-Neto 2004), que é adequado para seleção de grupo de genes quando o número de amostra é baixo (Sima, Attoor et al. 2005; Sima, Braga-Neto et al. 2005).Quality control of patient data, statistical analysis and graphs were performed using the Affymetrix MAS 5.0 program (Hubbell, Liu et al. 2002) and the open access R statistical package, version 2.5.0 (Ihaka 1996) and additional library, in particular the BioConductor library, version 1.16 (Gentleman, Carey et al. 2004). Dendograms and MDS graphics were produced with the functions R hclust and isoMDS, respectively, while the expression maps (heatmaps) were obtained with the functions hset.emap and heatmap. The p-values corresponding to two-tailed Welch's two-sample t test were obtained with the t-test function. Functional category analysis was performed with the EASE program (Expression Analysis Systematic Explorer) on the DAVID Bioinformatic website (http://david.abcc.ncifcrf.gov) (Dennis, Sherman et al. 2003). The classification method used a discriminant linear analysis implemented by directly estimating the average of samples and covariance matrices for each diagnostic class (Braga-Neto 2005). The classification accuracy was estimated by the potentiated resubstitution method (bolsted resubstitution, Braga-Neto 2004), which is suitable for selection of gene groups when the sample number is low (Sima, Attoor et al. 2005; Sima, Braga- Neto et al. 2005).
Exemplo 7 - Processamento dos dados de Microarranjos de DNAExample 7 - Processing of Microarray DNA data
Programa Affymetrix MAS 5.0 foi usado para escalonar os dados e produzir sinal e detection calls para os 54.675 genes em cada dos 26 microarranjos. Destes, 12.2999 foram considerados presentes (p<0.04) em todas os microarranjos, enquanto 20.365 não estavam presentes em nenhum dos microarranjos. Para manter apenas os genes promissores para futuras análises, foram empregados dois filtros não específicos: (i) filtro de detecção para eliminar genes não expressos, o que manteve apenas os genes considerados presentes em pelo menos 24 dos 26 microarranjos, resultando num total de 15.848 genes. Desta forma, foram tolerados 3.549 genes (15.848 - 12.299 = 3.549) que foram considerados ausentes em um ou dois microarranjos; (ii) filtro de variância para eliminar genes de expressão constitutiva, o que manteve os maiores 1/8 dos 15.848 genes previamente citados, resultando em 1981 genes com potencial prognóstico (Tabela 7) .Affymetrix MAS 5.0 program was used to scale the data and produce signal and detection calls for the 54,675 genes in each of the 26 micro arrays. Of these, 12,2999 were considered present (p <0.04) in all microarrays, while 20,365 were not present in any of the microarrays. To keep only the promising genes for future analyzes, two non-specific filters were used: (i) detection filter to eliminate unexpressed genes, which kept only the genes considered to be present in at least 24 of the 26 microarrays, resulting in a total of 15,848 genes. Thus, 3,549 genes (15,848 - 12,299 = 3,549) were tolerated, which were considered absent in one or two microarrays; (ii) variance filter to eliminate genes of constitutive expression, which kept the largest 1/8 of the 15,848 previously cited genes, resulting in 1981 genes with prognostic potential (Table 7).
Exemplo 8 - Análise exploratóriaExample 8 - Exploratory analysis
A Figura 3A mostra o dendograma para o agrupamento hierárquico dos 26 microarranjos de acordo com a expressão dos 1981 genes selecionados no estágio de pré-processamento. Foram empregados Average linkage e correlação de Pearson dos valores de expressão transformados em log. Foi observado que as amostras caíram em dois grandes grupos: o da direita contendo amostras ND e metade das amostras FD; enquanto o grupo da esquerda contem todas as amostras FHD , duas amostras ND (incluindo o outlier ND_199) e a outra metade dos pacientes FD. Este fato está de acordo com a intuição de que ND e FHD são os grupos mais diferentes e amostras FD formando um grupo intermediário. Isto é confirmado pelos gráficos de escalonamento multidimensional (MDS) em 2-D e 3-D para os 1981 genes, mostrados na Figura 3B e C. A medida de dissimilaridade usada foi 1 - r, onde r é a correlação de Pearson dos valores transformados em log. Microarranjos foram coloridos de acordo com a classe diagnostica. Pode-se observar que as amostras FHD constituem um grupo mais coeso do que as amostras ND, como esperado já que o grupo ND foi obtido de indivíduos com doença febril de etiologia desconhecida, enquanto as amostras FD podem ser divididas em dois grupos, um similar e um outro diferente de FHD, sendo este último mais próximo do grupo ND (esses são os dois grupos marcados na Figura 5). O baixo valor de stress (13.52% no gráfico 2-D e 7.32% no caso 3-D), particularmente no gráfico 3-D, significa que a estrutura delineante dos dados é intrinsecamente de baixa dimensão, o que indica que o pequeno número de assinaturas gênicas é capaz de representar o conteúdo discriminatório no dados.Figure 3A shows the dendrogram for the hierarchical grouping of the 26 microarrays according to the expression of the 1981 genes selected in the pre-processing stage. Average linkage and Pearson's correlation of expression values transformed into log were used. It was observed that the samples fell into two large groups: the one on the right containing ND samples and half of the FD samples; while the group on the left contains all FHD samples, two ND samples (including outlier ND_199) and the other half of FD patients. This fact is in agreement with the intuition that ND and FHD are the most different groups and FD samples forming an intermediate group. This is confirmed by the multidimensional scaling graphs (MDS) in 2-D and 3-D for the 1981 genes, shown in Figure 3B and C. The dissimilarity measure used was 1 - r, where r is the Pearson correlation of the values logged. Microarrays were colored according to the diagnostic class. It can be seen that FHD samples constitute a more cohesive group than ND samples, as expected since the ND group was obtained from individuals with febrile illness of unknown etiology, while FD samples can be divided into two groups, a similar and another one different from DHF, the latter being closer to the ND group (these are the two groups marked in Figure 5). The low stress value (13.52% in the 2-D graph and 7.32% in the 3-D case), particularly in the 3-D graph, means that the delineating structure of the data is intrinsically low in size, which indicates that the small number of gene signatures is capable of representing discriminatory content in the data.
Exemplo 9 - Análise de expressão diferencialExample 9 - Differential expression analysis
Foram realizados os testes estatísticos das diferenças entre as médias (Welch two-sample t-tests) para encontrar genes diferencialmente expressos entre os diferentes grupos diagnósticos. Foram consideradas duas principais comparações: FD versus FHD e dengue (FD + FHD) versus ND. A primeira comparação corresponde as 18 amostras oriundas dos pacientes comprovadamente infectados com vírus da dengue e é a mais importante comparação para a presente invenção, pois esta discrimina entre a forma benigna (FD) e maligna (FHD) da doença. Importantes genes usados para caracterizar estas duas manifestações clínicas assim como aqueles específicos para infecção pelo vírus da dengue são mostrados nas Tabelas 2 e 3. Gráfico de vulcão na Figura 4 e a correspondente lista de genes (Tabelas 2 e 3) mostram que os valores p correlacionam bem com magnitude de diferença de expressão (fold-change) em ambas as situações analisadas.Statistical tests of the differences between the means (Welch two-sample t-tests) were performed to find genes differentially expressed between the different diagnostic groups. Two main comparisons were considered: FD versus FHD and dengue (FD + FHD) versus ND. The first comparison corresponds to the 18 samples from patients proven to be infected with dengue virus and is the most important comparison for the present invention, since it discriminates between the benign (FD) and malignant (FHD) forms of the disease. Important genes used to characterize these two clinical manifestations as well as those specific for dengue virus infection are shown in Tables 2 and 3. The volcano graph in Figure 4 and the corresponding list of genes (Tables 2 and 3) show that the p values correlate well with magnitude of difference of expression (fold-change) in both situations analyzed.
A Figura 5 mostra o mapa de expressão (heatmap) para os melhores 40 genes que discriminam as amostras FD de FHD, de acordo com critério de Welch t-test, assim como o agrupamento hierárquico e gráficos MDS para os 40 melhores genes discriminatórios entre FD e FHD. A Tabela 4 mostra os resultados da análise da representação de categoria funcional da lista dos melhores 40 genes discriminatórios entre FD e FHD com o programa EASE como descrito no Exemplo 6. A análise indicou o enriquecimento de certas categorias de genes. Cinco categorias apresentaram scores significantes (p<0.05) após a correção de Benferroni para múltiplos testes, incluindo aqueles envolvidos na resposta imune e defesa, resposta a estímulos bióticos, ligação a cobre/cádmio e homeostase do ion cobre (Tabela 4).Figure 5 shows the heatmap for the best 40 genes that discriminate FD samples from FHD, according to Welch t-test criteria, as well as the hierarchical grouping and MDS graphs for the 40 best discriminatory genes among FD and FHD. Table 4 shows the results of the analysis of the functional category representation of the list of the best 40 discriminatory genes between FD and FHD with the EASE program as described in Example 6. The analysis indicated the enrichment of certain categories of genes. Five categories had significant scores (p <0.05) after Benferroni's correction for multiple tests, including those involved in immune and defense responses, response to biotic stimuli, binding to copper / cadmium and home ionization of copper ion (Table 4).
Exemplo 10 - Identificação dos genes classificadoresExample 10 - Identification of classifying genes
Além da seleção univariada realizada por testes t, foi realizada a seleção exaustiva (todas as possíveis combinações) de genes isolados, bem como duplas e trios a partir dos 10981 genes, usando análise de discriminação linear e resubstituição potencializada. A Tabela 5 mostra os classificadores baseados em 1, 2 ou 3 genes, ranqueados pelo erro de classificação estimado. Há 37 únicos genes entre os melhores 40 pares, enquanto há 87 únicos genes entre os melhores 100 trios classificadores. A lista dos trios de genes é dominada pelos genes PSMB9, MT2A, e LOC400368. Na verdade, apenas um trio não contém qualquer desses três, este é SFRS5, PDCD4, MKNK2, cujo erro estimado é de 0.0383. As médias para o erro estimado dos melhores classificadores são:In addition to the univariate selection carried out by t-tests, exhaustive selection (all possible combinations) of isolated genes was carried out, as well as doubles and trios from the 10981 genes, using linear discrimination analysis and potentiated resubstitution. Table 5 shows the classifiers based on 1, 2 or 3 genes, ranked by the estimated classification error. There are 37 unique genes among the best 40 pairs, while there are 87 unique genes among the best 100 classifying trios. The list of the gene trios is dominated by the PSMB9, MT2A, and LOC400368 genes. In fact, only one trio does not contain any of these three, this is SFRS5, PDCD4, MKNK2, whose estimated error is 0.0383. The averages for the estimated error of the best classifiers are:
indica que a classificação com pares de genes é mais acurado do que genes individuais, enquanto a classificação com tripla de genes é mais precisa do que com pares (a margem de erro acima se refere ao intervalo de confidência de 95%) . A seleção com dois e três genes têm o potencial de recuperar genes que usando métodos univariados (tais como test-t) não é possível recuperar. Isto é possível se perceber na lista dos melhores classificadores com 2 genes, por exemplo, o gene HLA-F (que é menos expresso em FHD do que FD) . A Figura 6 mostra o gráfico para o classificador com 2 genes PSMB9 e MT2A. A probabilidade estimada de erro em futuros dados é de 5.38%. Neste caso, a menor expressão de ambos os genes é assinatura de FHD, enquanto maior expressão de ambos os genes é característico de FD.indicates that classification with pairs of genes is more accurate than individual genes, while classification with triple genes is more accurate than with pairs (the above margin of error refers to the 95% confidence interval). Selection with two and three genes has the potential to retrieve genes that using univariate methods (such as t-test) cannot be retrieved. This can be seen in the list of the best classifiers with 2 genes, for example, the HLA-F gene (which is less expressed in FHD than FD). Figure 6 shows the graph for the classifier with 2 genes PSMB9 and MT2A. The estimated probability of error in future data is 5.38%. In this case, the lowest expression of both genes is FHD signature, while the highest expression of both genes is characteristic of FD.
Exemplo 11 - Validação dos dados de microrranjos usando PCR em tempo real quantitativoExample 11 - Validation of micro array data using quantitative real-time PCR
Ensaios de PCR em tempo real quantitativo (qPCR) foram realizados para validar os resultados obtidos nos ensaios de microarranjos. Foram selecionados os seguintes genes: PSMB9, MT2A, HLA-F and C3aRl, cuja expressão foi predominante em amostras FD comparado às amostras FHD. qPCRs dos genes acima citados foram realizados usando oito amostras FD e oito FHD obtidas dos mesmos pacientes testados nos ensaios de microarranjos. De acordo com a Figura 7A, a quantificação por qPCR mostrou uma boa correlação com os dados dos microarranjos. Além disso, qPCR foi também realizado num grupo de amostra independentes das amostras utilizadas nos ensaios de microarranjos, coletadas dentro de 11 dias do inicio dos sintomas e antes do inicio dos sintomas de vasculopatia. Os resultados de qPCR também indicaram que os níveis de expressão dos genes selecionados foram mais reduzidos em FHD do que em FD, corroborando com os resultados obtidos com o modelo 2D mostrado na Figura 3. Com isso, cada um dos quatro genes foram expressos em menor quantidade emQuantitative real-time PCR (qPCR) assays were performed to validate the results obtained in the microarray assays. The following genes were selected: PSMB9, MT2A, HLA-F and C3aRl, whose expression was predominant in FD samples compared to FHD samples. qPCRs of the aforementioned genes were performed using eight FD and eight FHD samples obtained from the same patients tested in the microarray assays. According to Figure 7A, quantification by qPCR showed a good correlation with the microarray data. In addition, qPCR was also performed on a sample group independent of the samples used in the microarray assays, collected within 11 days of the onset of symptoms and before the onset of symptoms of vasculopathy. The results of qPCR also indicated that the expression levels of the selected genes were more reduced in FHD than in FD, corroborating the results obtained with the 2D model shown in Figure 3. With this, each of the four genes were expressed in lesser quantity in
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Tabela 2. Lista de genes mostrados no gráfico vulcão Dengue (FD+FHD) vs. ND de acordo com fold change e valor p.Table 2. List of genes shown in the Dengue volcano graph (FD + FHD) vs. ND according to fold change and p-value.
family A, member 6family A, member 6
frame 24frame 24
7.450867.45086
7.457367,45736
7.401557.40155
7.250527.25052
7.381967.38196
7.143287.14328
5.948505,94850
6.279966.27996
7.324217.32421
6.806046,80604
6.419556.41955
6.711836.71183
7.418727.41872
6.330806,33080
7.537737,53773
7.044407.04440
6.830806.83080
6.360356,36035
7.284247,28424
8.226908.22690
6.350576,35057
6.424556.42455
7.464907.46490
7.861197.86119
6.847676.84767
7.127437,12743
7.305657.30565
6.195826,19582
6.482766.48276
7.239237.23923
6.988576.98857
8.675808.67580
6.783886.78388
Tabela 3. Lista de genes mostrados no gráfico vulcão FD vs.Table 3. List of genes shown in the FD vs. volcano graph.
FHD de acordo com fold change e valor p.FHD according to fold change and p-value.
factor 1factor 1
superfamily, member 17superfamily, member 17
(calcyclin)(calcyclin)
Tabela 4. Análise EASE da abundância funcional da lista dosTable 4. EASE analysis of functional abundance from the list of
4Ί4Ί
Tabela 5. Classificadores baseados em genes individuais, duplas ou trios ranqueados pelo erro estimado.Table 5. Classifiers based on individual, double or triple genes ranked by the estimated error.
Gene 3 Erro EstimadoGene 3 Estimated Error
0.08700.0870
0.09270.0927
0.11820.1182
0.12020.1202
0.12770.1277
0.13010.1301
0.13140.1314
0.13650.1365
0.13890.1389
0.14430.1443
0.14770.1477
0.15130.1513
0.15550.1555
0.16040.1604
0.16260.1626
0.16340.1634
0.16690.1669
0.16740.1674
0.16880.1688
0.16950.1695
0.17080.1708
0.17290.1729
0.17340.1734
0.17490.1749
0.17670.1767
0.17720.1772
0.17930.1793
0.18210.1821
0.18500.1850
0.18810.1881
0.18850.1885
0.18930.1893
0.19100.1910
0.19200.1920
0.19330.1933
0.19410.1941
0.19560.1956
0.19630.1963
0.19660.1966
0.19700.1970
0.03510.0351
0.04960.0496
0.05010.0501
Tabela 6. Lista dos 73 genes diferencialmente expressos entre casos de FD e FHD que foram, comuns entre aqueles 200 mais significantes genes de acordo com o teste Welch's t-test e osTable 6. List of 73 genes differentially expressed between cases of FD and DHF that were common among those 200 most significant genes according to the Welch's t-test and the
200 genes com maiores fold-change da média de expressão dos níveis de RNAm.200 genes with greater fold-change in the average expression of mRNA levels.
inducible, 67kDa /// guanylate binding protein 1, interferon-inducible, 67kDainducible, 67kDa /// guanylate binding protein 1, interferon-inducible, 67kDa
(UBC7 homolog, yeast)(UBC7 homolog, yeast)
TNFSF1 necrosis factor (ligand) superfamily,TNFSF1 necrosis factor (ligand) superfamily,
2- member 12-member 132- member 12-member 13
TNFSF1TNFSF1
6.3346,334
8.27888.2788
6.85786,8578
7.42547.4254
7.4087,408
7.21847.2184
7.51917.5191
7.39687.3968
7.57267.5726
6.92976,9297
7.89997.8999
6.55496.5549
6.51826.5182
6.6286,628
7.20257,2025
7.12247,124
6.68646.6864
7.03577.0357
7.06117.0611
(calcyclin)(calcyclin)
Tabela 7. Lista dos 1981 genes após o processamento dos dados de microarranjo.Table 7. List of 1981 genes after processing microarray data.
LOC64274LOC64274
LOC43999LOC43999
M0RF4L1M0RF4L1
HNRNPA2 BIHNRNPA2 BI
ΡΡ
ΊΟΊΟ
RNASET2RNASET2
M0BKL1 ΒM0BKL1 Β
LOC28366LOC28366
LOC54147LOC54147
LOC44055LOC44055
Λ»Λ »
SERPINASERPINA
subcomponsubcompon
LOC39250LOC39250
CDC42SECDC42SE
LOC55289LOC55289
ARHGAP1ARHGAP1
ΡΡ
HIST1H3 ΗHIST1H3 Η
100100
/5/ 5
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