TWI857353B - A method to assess whether individuals are overexposed to fine particulate matters (pm2.5) - Google Patents

Abstract

The present invention provides a method for determining the exposure of biological individuals to Fine Particulate Matters (PM2.5), which can be applied for early diagnosis and detection of cancer, cognitive impairment and autoimmune diseases caused by Fine Particulate Matters (PM2.5). The detected gene disclosed of the present invention comprises: OXR1, PRPF38B, ITGAM, FAM102B, PHF8, CD151, DIAPH2, PPP2R1B, TMEM19, CLK4, MED15, DYRK1B, ZKSCAN5, UNK, ZNF280C, UBE4A, ACLY, R3HDML, CEP170, ZBTB4, NSD1, CEP250, OLFM1, ATXN7L1, CDADC1, MYO18A, INSTS6L, CCR2, TFDP2, RARA, BLVRA, GAPT, CHD9 and SNX10.

Description

A method for assessing whether an individual is overexposed to fine particulate matter PM2.5

The present invention discloses a method for determining whether a biological individual is exposed to fine suspended particulate matter PM2.5, which can be applied to the early determination and detection of cancer, cognitive impairment and autoimmune diseases caused by fine suspended particulate matter PM2.5.

The World Health Organization defines air pollution as any chemical, physical or biological agent that alters the natural characteristics of the atmosphere, whether indoors or outdoors. Common sources of air pollution include household combustion equipment, motor vehicles, industrial facilities and forest fires. The main pollutants that affect public health issues include particulate matter (PM), carbon monoxide, ozone, nitrogen dioxide and sulfur dioxide. Outdoor and indoor air pollution can cause respiratory and other diseases and is an important factor in morbidity and mortality.

Air pollution kills about 7 million people worldwide each year. According to the World Health Organization, 99% of the world's population breathes air that exceeds WHO guideline limits, with exposure highest in low- and middle-income countries. Air pollution poses a major threat to health and climate. The combined effects of ambient and household air pollution lead to millions of premature deaths each year, primarily due to increased mortality from stroke, heart disease, chronic obstructive pulmonary disease (COPD), lung cancer, and acute respiratory infections.

In the WHO global air quality guidelines published in September 2021, PM2.5 and PM10 are the primary sources of pollution to be controlled (Geneva: World Health Organization; 2021.Licence: CC BY-NC-SA 3.0 IGO.). PM is a complex mixture whose components have different chemical and physical properties. This heterogeneity makes the study of PM exposure and risk complicated. The size and physical properties, chemical composition and source of PM also vary, and the impact caused by PM is the most serious.

Aerodynamics uses aerodynamic diameter as a general indicator of particle size. Suspended particles with a diameter less than or equal to 2.5μm are PM2.5. The guidelines state that annual exposure to PM2.5 should not exceed 5μg/ ^m3 , and short-term exposure to PM2.5 should not exceed 15μg/ ^m3 in 24 hours. Long-term exposure to PM2.5 (several months to several years) will affect health, resulting in increased all-cause mortality, cardiovascular disease, respiratory system and lung cancer mortality. Literature points out that PM2.5 components can cause systemic harm to the human body, such as cardiovascular disease, inflammatory response, cancer, lung respiratory disease, and even cognitive impairment, dementia, etc., causing human health to be affected.

Biomarker detection is an important method for precision medicine and will help prevent, diagnose and monitor diseases. Air pollution has a huge impact on citizens around the world. Using biomarkers to detect the possible harm caused by air pollution as a health prediction and warning will help prevent and control air pollution.

The characteristics of many cancers or disease states can be determined by changes in the transcription of specific genes, which can reveal differences in the expression of various genes. Tumor-causing oncogenes and tumor suppressor genes that affect cancer can cause an increase or decrease in the expression of many genes. Therefore, changes in the expression (transcription) of specific genes can be used as biomarkers for the occurrence or progression of various cancers or diseases.

However, the environment is full of PM2.5, which is unavoidable in most cities nowadays. Therefore, how to determine whether an individual is overexposed to PM2.5 is a key issue. Since the detection of PM2.5 in the environment may not reflect the amount of PM2.5 absorbed by the organism, a more direct evaluation and judgment method is needed.

Until now, although it is known that cancer, cognitive impairment and autoimmune diseases caused by air pollution are related, the biomarkers of specific genes or specific gene combinations that change their expression patterns are still unknown. The present invention uses transcriptome analysis methods to explore biomarker genes related to air pollution effects, and uses differentially expressed gene (DEG) analysis methods to diagnose or predict the development, diagnosis and prediction of diseases related to air pollution or PM2.5.

The present invention uses RNA sequencing to explore novel biomarkers related to air pollution. This method can perform high-throughput sequencing and analysis on all mRNA in the sample, and compare the changes in transcriptome (gene expression) under different experimental conditions, and then find differential genes after transcriptome analysis. This method can be used to discover novel biomarkers related to the effects of air pollution, which can be used as early warning, diagnosis and monitoring of air pollution effects and its detection method, for the purpose of air pollution prevention and control.

The present invention discloses a method for evaluating whether an individual is overexposed to fine particulate matter PM2.5, comprising at least the following steps: (a) providing a sample obtained from the individual; (b) determining the gene expression level of at least one target gene in the sample, wherein the at least one target gene comprises at least one of the following: OXR1, PRPF38B, ITGAM, PPP2R1B and FAM102B; and (c) comparing the gene expression level of the at least one target gene in step (b) with that of a control group, wherein when the gene expression level of the OXR1, or the PRPF38B, or the ITGAM, or the PPP2R1B, or the FAM102B is higher than that of the control group, it is evaluated that the individual is overexposed to fine particulate matter PM2.5.

The at least one target gene disclosed in the present invention further comprises: PHF8, DYRK1B, ZKSCAN5, DIAPH2, UBE4A, ACLY, NSD1, R3HDM1, CEP250, ATXN7L1, CD151, BLVRA, CCR2, INTS6L, MYO18A and RARA, wherein when the PHF8, or the DYRK1B, or the ZKSCAN5, or the D When the expression level of IAPH2, or the UBE4A, or the ACLY, or the NSD1, or the R3HDM1 gene is lower than that of the control group, or when the expression level of CEP250, or the ATXN7L1, or the CD151, or the BLVRA, or the CCR2, or the INTS6L, or the MYO18A, or the RARA gene is higher than that of the control group, it is assessed that the individual is over-exposed to fine suspended particulate matter PM2.5.

At least one target gene disclosed in the present invention further includes: TMEM19, CLK4, MED15, UNK, ZNF280C, CEP170, ZBTB4, OLFM1, CDADC1, TFDP2, GAPT, CHD9 and SNX10. When the expression level of the TMEM19, CLK4, MED15, UNK, ZNF280C, CEP170 or ZBTB4 gene is lower than that of the control group, or when the expression level of the OLFM1, CDADC1, TFDP2, GAPT, CHD9 or SNX10 gene is higher than that of the control group, the individual is assessed to be overexposed to fine suspended particulate matter PM2.5.

The control group refers to the gene expression results detected by the same gene expression experiment conducted on healthy individuals.

The term "higher than" in the present invention's "gene expression level is higher than the control group" means that the detected gene expression level is higher than the gene expression level of the control group by 1%, 3%, 5%, 10% or more.

The term "lower than" in the present invention's "gene expression level is lower than that of the control group" means that the detected gene expression level is lower than 1%, 3%, 5%, 10% or more than 10% of the gene expression level of the control group.

The method for determining at least one target gene disclosed in the present invention includes polymerase chain reaction, real-time polymerase chain reaction, quantitative real-time reverse transcription polymerase chain reaction, droplet digital polymerase chain reaction, nested polymerase chain reaction, whole genome sequencing, enzyme-linked immunosorbent assay, Western blot, enzyme immunoassay, lateral flow immunochromatography or flow cytometer.

The individual samples disclosed in the present invention include blood, plasma, serum, urine, feces, ascites, sputum, oral mucosal cells, gastric juice, bile, tissue, cells, organs, body fluids or any combination thereof.

The present invention also discloses a detection kit for detecting excessive exposure of an individual to fine particulate matter PM2.5, comprising more than one set of biomarker primers, wherein the genes identified by the biomarker primers include: OXR1, PRPF38B, ITGAM, PPP2R1B and FAM102B; a detection reagent; and a control group sample.

The genes identified by more than one set of biomarker primers disclosed in the present invention further include: PHF8, DYRK1B, ZKSCAN5, DIAPH2, UBE4A, ACLY, NSD1, R3HDM1, CEP250, ATXN7L1, CD151, BLVRA, CCR2, INTS6L, MYO18A and RARA.

The genes identified by the above-mentioned set of biomarker primers disclosed in the present invention further include: TMEM19, CLK4, MED15, UNK, ZNF280C, CEP170, ZBTB4, OLFM1, CDADC1, TFDP2, GAPT, CHD9 and SNX10.

Figure 1 shows the organ changes in mice after being treated with PM2.5 fine particle samples.

Figure 2 shows the summary results of sample transcript RNA sequencing.

Figure 3 shows the sample KEGG-affected metabolic pathways.

Figure 4 shows the effect of PM2.5 suspended particles on the gene expression of human monocytic cell line (THP-1) at 48 hours.

Figure 5 shows the effect of 10μM benzo[a]pyrene on gene expression in human monocytic cell line (THP-1) at 48 hours.

Figure 6 shows the differences in genes OXR1, PRPF38B, ITGAM, PPP2R1B and FAM102B between Kaohsiung and Hualien test specimens.

Figure 7 shows the flow chart for establishing the air pollution detection algorithm of the present invention.

In the following, preferred embodiments of the present disclosure will be described in detail with reference to the attached drawings. The detailed description of the disclosure in combination with the attached drawings is an exemplary embodiment of the present disclosure and does not limit the embodiments in which the present invention can be implemented. The following detailed description includes specific details to provide a comprehensive understanding of the present invention. However, a person of ordinary skill in the art can implement the present disclosure without these specific details.

The following implementation examples are not restrictive and merely represent various aspects and features of the present invention.

Example 1: Collection and extraction of fine suspended particulate matter PM2.5 samples

Using a high-flow fully automatic suspended particle sampler (Digitel DHA-80), it was set up at Kaohsiung Xiaogang from January 19 to March 3, 2018 to collect PM2.5 fine suspended particles. The collected fine suspended particle pollutants were then filtered, crushed, distilled, and freeze-dried to complete the collection of PM2.5.

Finally, 18 pieces of filter paper were collected, with a total weight of 1.043 grams. After ultrasonic vibration extraction, 0.902 grams of PM2.5 suspended particles were obtained, with a recovery rate of 86.5%.

The collected PM2.5 fine particles were analyzed for composition, and the total content of polycyclic aromatic hydrocarbons was 32.2ng/mg, the total content of metals was 48.3g/mg, and the total content of cations and anions was 714.7g/mg.

Among the metal components, sodium, potassium, aluminum, zinc, barium, iron, and magnesium have the highest content; among the polycyclic aromatic hydrocarbon compounds, benzo(g,h,i)peryene, benzo(b)fluoranthrene, benzo[a]pyrene, indeno(1,2,3-cd)pyrene, and coronene have the highest content; among the cation and ion ions, nitrate, sulfate, and ammonium ions have the highest content. The component analysis tables are shown in Table 1, Table 2, and Table 3.

Example 2: PM2.5 suspended particle mouse model

PM2.5 was suspended in sterile water and administered to 8-week-old C57BL/6 male mice by oropharyngeal instillation. The dose administered to each mouse was 25 μg per time, the volume administered was 30 μL, and the injection frequency was twice a week. After continuous exposure of the mice for 24 weeks, the mice were sacrificed and various samples were collected for analysis.

After mice were continuously exposed to PM2.5 fine suspended particles in Kaohsiung, they showed inflammation in their lungs, thickening of the walls of pulmonary arteries, significantly faster heart rates, and increased diastolic and systolic blood pressures.

As shown in Figure 1, in terms of organ changes, the weight of the pancreas and lungs increased significantly and abnormally.

Example 3: PM2.5 fine suspended particle sample transcript analysis

After the mice were exposed to PM2.5 suspended particles in Kaohsiung Xiaogang for 24 weeks, blood samples were taken from the mice, and total RNA was extracted from the buffy coat of the blood, which contains white blood cells and platelets. Transcriptome RNA sequencing and analysis were then performed. There were 4 mice in each of the control group and PM2.5 exposure group.

As shown in Figure 2, the control group C4, C10, C12, and C16 are mice that were not exposed to PM2.5, and the experimental group P9, P17, P18, and P21 are mice that were exposed to PM2.5. Two patterns can be distinguished in the heat map, and the gene expression has a consistent trend.

Among them, a total of 3677 genes had expression differences, 1489 genes had higher expression levels due to up-regulation, and 2188 genes had lower expression levels due to down-regulation.

As shown in Figure 3, KEGG analysis shows the association between the affected genes and metabolic pathways related to cancer or other diseases.

Example 4: Design of primers for transcriptional expression genes related to PM2.5 fine particle exposure

In the analysis of the transcriptome of mice exposed to PM2.5, the present invention found that the 34 genes with different expression levels were PHF8, TMEM19, CLK4, DIAPH2, MED15, DYRK1B, ZKSCAN5, UNK, ZNF280C, UBE4A, ACLY, R3HDML, CEP170, ZBTB4, NSD1, CEP250, OLFM1, FAM102B, CD151, ITGAM, ATXN7L1, PPP2R1B, PRPF38B, OXR1, CDADC1, MYO18A, INSTS6L, CCR2, TFDP2, RARA, BLVRA, GAPT, CHD9 and SNX10.

Among the 34 genes, those with increased expression levels were CEP250, OLFM1, FAM102B, CD151, ITGAM, ATXN7L1, PPP2R1B, PRPF38B, OXR1, CDADC1, MYO18A, INSTS6L, CCR2, TFDP2, RARA, BLVRA, GAPT, CHD9 and SNX10, a total of 19 genes.

Among the 34 genes, those with decreased expression levels were PHF8, TMEM19, CLK4, DIAPH2, MED15, DYRK1B, ZKSCAN5, UNK, ZNF280C, UBE4A, ACLY, R3HDML, CEP170, ZBTB4 and NSD1, a total of 15 genes.

The primer comparison table of 34 genes is shown in Table 4 and Table 5 below. The completed primer pairs were used to design real-time quantitative polymerase chain reaction.

The present invention uses differential expression gene (DEG) analysis to analyze the gene expression differences in the transcriptome of mice after PM2.5 exposure. It shows that 34 genes are most related to the effects of PM2.5, of which 15 genes are genes with decreased expression, as shown in Table 6 below; and 19 genes are genes with increased expression, as shown in Table 7 below.

Analysis of gene expression differences. The control group is C4, C10, C12, and C16, mice that have not been exposed to PM2.5. The test group is P9, P17, P18, and P21, mice that have been exposed to PM2.5. The results of the two groups are compared. log2FoldChange is the difference fold. Negative values are displayed as the difference fold of decreased expression, and positive values are the difference fold of increased expression. lfcSE is the standard deviation. The smaller the corrected p-value (padj), the more significant the difference. Generally speaking, padj<0.05 is the best. The padj values of each gene in Table 6 and Table 7 below are all <0.05, indicating high credibility.

Example 4: PM2.5 suspended particles on human monocyte model

Human monocytic cell lines were treated with 50μg/ml PM2.5 and 10μM benzo[a]pyrene, and RNA was further extracted and cDNA was transcribed. Expression analysis was performed using qPCR, and several genes showed significant differences in expression compared with the control group.

The steps of qPCR analysis are as follows: the total reaction volume is 20μL, of which 10μL 2X SYBR Green is premixed with real-time fluorescent quantitative polymerase enzyme reaction (Bio-Rad iTaq Universal SYBR Green Supermix), each pair of primers is 0.2μM and reverse transcribed with cell RNA as cDNA template, react at 95℃ for 2 minutes, 95℃ for 15 seconds, 60℃ for 30 seconds, and repeat the above steps for 40 cycles.

The calculation method is to calculate the Ct value of qPCR. The Ct value of the biomarker target gene minus the Ct value of the internal control gene (internal control) is dCt (delta Ct; △Ct); the dCt of the PM2.5 treatment group minus the dCt of the control group is ddCt (delta delta Ct; △△Ct).

Then, we use the formula: 2-△△Ct to obtain the expression levels related to control in Figures 4 and 5.

The expression level of the target gene is determined by the threshold cycle number (Ct) value. As shown in Figure 4, when human monocytic cell lines were treated with PM2.5 particles for 48 hours, the genes with greater expression differences included PHF8, DYRK1B, and ZKSCAN5, which were genes with decreased expression levels, and OXR1, CEP250, PRPF38B, ATXN7L1, PPP2R1B, CD151, FAM102B, BLVRA, CCR2, INTS6L, MYO18A, and RARA, which were genes with increased expression levels.

As shown in Figure 5, after 48 hours of treatment with 10μM benzo[a]pyrene, genes with greater expression differences included PHF8, DIAPH2, UBE4A, ZKSCAN5, ACYL, NSD1, R3HDM1, which were genes with decreased expression, and ITGAM, OXR1, CD151 and FAM102B, which were genes with increased expression.

As shown in Figures 4 and 5, genes with differential expression levels after high concentration 10μM benzo[a]pyrene treatment include DIAPH2, UBE4A, ACLY, NSD1, R3HDM1 and ITGAM genes, while these genes showed no expression differences when only PM2.5 was treated.

Among them, the DIAPH2 gene is related to the occurrence of aerodigestive tract epidermal squamous cell carcinoma.

Among them, the CD151 gene is related to the occurrence of non-small cell lung cancer.

Among them, the PHF8 gene is associated with cognitive impairment and behaviors related to depression and anxiety.

Among them, the DYRK1B gene is related to breast cancer and metabolic diseases.

Among them, the ZKSCAN5 gene is related to breast cancer, colorectal cancer, etc.

Among them, the OXR1 gene is related to esophageal squamous cell carcinoma and neural degeneration.

Among them, the CEP250 gene is related to retinal disease.

Among them, the PRPF38B gene is related to the occurrence of breast cancer and gastric cancer.

Among them, the ATXN7L1 gene may be related to lung cancer.

Among them, the PPP2R1B gene is related to lung cancer, gastric cancer, liver cancer, cervical cancer and ovarian cancer.

Among them, the ITGAM gene is related to the occurrence of systemic lupus erythematosus.

Among them, the FAM102B gene is related to the occurrence of rheumatoid arthritis.

Among them, BLVRA is associated with colorectal cancer and neonatal jaundice.

Among them, the study of CCR2 gene and its receptor antagonist found that it can reduce the occurrence of clinical inflammatory response.

Among them, INTS6L is related to liver cancer, prostate cancer, and colorectal cancer.

Among them, the present invention discloses that the expression of OXR1, PRPF38B, ITGAM, PPP2R1B, FAM102B, CEP250, ATXN7L1, CD151, BLVRA, CCR2, INTS6L, MYO18A or RARA genes is increased after being induced by PM2.5 fine suspended particles.

The present invention reveals that the expression level of PHF8, DIAPH2, UBEA4A, DYRK1B, ZKSCAN5, ACLY, NSD1 or R3HDM1 genes is decreased after being induced by PM2.5 fine suspended particles.

Example 5: Analysis of the expression of air pollution biomarkers in human specimens

This invention collects 234 and 247 human blood and urine samples from Kaohsiung Municipal Siaogang Hospital and Hualien Tzu Chi Hospital, respectively. The samples from Siaogang Hospital and Hualien Tzu Chi Hospital represent the high and low exposure groups to air pollution, respectively. The subjects also took questionnaires, physiological functions (such as cardiopulmonary function), and blood and urine tests while sampling, so as to further distinguish the physical conditions of high and low exposure to air pollution. The clinical samples are ultimately the results of the classification of the samples through objective physiological analysis and subjective questionnaires, and possible interference factors such as smoking are also excluded.

For the elderly subjects, the air pollution exposure was also assessed using the Hybrid Kriging and Land use regression model to estimate the monthly air pollution concentration at their homes. After reconfirmation, the high and low exposure elderly groups in Kaohsiung and Hualien were defined.

Blood samples (cDNA preservation) from the elderly in Hualien and Kaohsiung were screened, with 234 and 247 samples respectively. The screening condition was first based on the internal control gene GAPDH Ct value <28 in the qPCR results. The two regions represent the low-altitude pollution exposure and high-altitude pollution exposure groups, respectively.

The cDNA expression level of blood samples was measured by qPCR reaction. The reaction conditions and steps were as follows: the total reaction volume was 20 μL, of which 10 μL 2X SYBR Green was premixed with real-time fluorescent quantitative polymerase enzyme reaction (Bio-Rad iTaq Universal SYBR Green Supermix), each primer pair was 0.2 μM and reverse transcribed with cell RNA as cDNA template, reacted at 95°C for 2 minutes, 95°C for 15 seconds, and 60°C for 30 seconds, and the above steps were repeated for a total of 40 cycles.

As shown in Figure 6, the gene expression levels of the target genes OXR1, PRPF38B, ITGAM, PPP2R1B, and FAM102B in the blood sample analysis are significantly different, and can be used as an indicative biomarker for air pollution warning. The relative gene expression in Figure 6 is represented by △Ct, and the larger the value, the lower the expression level.

Example 6: Air pollution biomarker combination using algorithm analysis

The present invention establishes an air pollution detection algorithm model based on the gene expression levels of target genes OXR1, PRPF38B, ITGAM, PPP2R1B, and FAM102B.

As shown in Figure 7, after collecting samples from the elderly population exposed to air pollution, the gene expression difference △Ct of the above qPCR results was used to build a model. The sample △Ct was randomly selected and allocated according to the two groups of high exposure and low exposure. The training set was first used for information training, and then the prediction model was established. After the model was completed, the testing set was used as the unknown data to test the stability of the model, and the feasibility was evaluated by retesting until the model was completed.

The algorithm analysis used in the present invention is modeled on two algorithms: logistic regression and decision tree.

Table 8. Results of two algorithm models: logical regression and classification tree

The results in Table 8 show the following meanings: Accuracy is defined as the percentage of correctly predicted results in the total samples; Sensitivity is the ratio of positive detection among patients with the disease; Specificity is the ratio of negative detection among patients without the disease; Precision is defined as the ratio of positive detection among all samples predicted to be positive; F1-Score is an indicator to measure the accuracy of the binary classification model, which is the harmonic mean of precision and recall (recall is sensitivity); AUC (Area Under the Curve) is a commonly used statistical value for the prediction ability of the classifier. In the algorithm, a threshold is used to determine whether a patient is sick. The threshold directly affects the sensitivity and specificity. The distribution of sensitivity and specificity can be used to make the ROC Curve (Receiver operating characteristic curve). The area under the ROC Curve is called AUC (Area Under Curve). The larger the AUC value, the better the decision-making effect.

Explanation of two algorithm models: logical regression and classification tree.

Table 9. Logical regression algorithm results

Logical regression is a linear regression output method used to determine whether the data attribute is classified as high or low exposure to air pollution. The output value of the regression line is >=0 or <0, which is one of the two categories. β is the coefficient; S.E. (Square Error) is the square error.

The five target genes OXR1, PRPF38B, ITGAM, PPP2R1B, and FAM102B were calculated by logical regression, and the final formula was: 6.928-0.166*OXR1-0.173*ITGAM+0.298*FAM102B-0.272*PRPF38B-0.155*PPP2R1B>-0.07493124. The target genes in the formula all represent the △Ct value after the test. If the test result is >-0.07493124, it means that it is predicted to be high-altitude pollution exposure.

The present invention discloses a method for evaluating whether an individual is overexposed to fine particulate matter PM2.5, comprising at least the following steps: (a) providing a sample obtained from the individual; (b) determining the gene expression level of at least one target gene in the sample, wherein the at least one target gene comprises at least one of the following: OXR1, PRPF38B, ITGAM, PPP2R1B and FAM102B; and (c) comparing the gene expression level of the at least one target gene in step (b) with that of a control group, wherein when the gene expression level of the OXR1, or the PRPF38B, or the ITGAM, or the PPP2R1B, or the FAM102B is higher than that of the control group, it is evaluated that the individual is overexposed to fine particulate matter PM2.5.

The present invention discloses a method for evaluating whether an individual is overexposed to fine particulate matter PM2.5, wherein the at least one target gene further comprises: PHF8, DYRK1B, ZKSCAN5, DIAPH2, UBE4A, ACLY, NSD1, R3HDM1, CEP250, ATXN7L1, CD151, BLVRA, CCR2, INTS6L, MYO18A and RARA, wherein when the PHF8 or the DYRK1 B, or the ZKSCAN5, or the DIAPH2, or the UBE4A, or the ACLY, or the NSD1, or the R3HDM1 gene expression level is lower than that of the control group, or the CEP250, or the ATXN7L1, or the CD151, or the BLVRA, or the CCR2, or the INTS6L, or the MYO18A, or the RARA gene expression level is higher than that of the control group, the individual is assessed to be overexposed to fine suspended particulate matter PM2.5.

The present invention discloses a method for evaluating whether an individual is overexposed to fine suspended particulate matter PM2.5, wherein the at least one target gene further comprises: TMEM19, CLK4, MED15, UNK, ZNF280C, CEP170, ZBTB4, OLFM1, CDADC1, TFDP2, GAPT, CHD9 and SNX10. When the expression level of the TMEM19, or the CLK4, or the MED15, or the UNK, or the ZNF280C, or the CEP170, or the ZBTB4 gene is lower than that of the control group, or when the expression level of the OLFM1, or the CDADC1, or the TFDP2, or the GAPT, or the CHD9, or the SNX10 gene is higher than that of the control group, it is evaluated and determined that the individual is overexposed to fine suspended particulate matter PM2.5.

The present invention also discloses a detection kit for detecting excessive exposure of an individual to fine particulate matter PM2.5, comprising more than one set of biomarker primers, wherein the genes identified by the biomarker primers include: OXR1, PRPF38B, ITGAM, PPP2R1B and FAM102B; a detection reagent; and a control group sample.

The present invention also discloses a detection kit for detecting excessive exposure of an individual to fine particulate matter PM2.5, wherein the genes identified by the biomarker primers further include: PHF8, DYRK1B, ZKSCAN5, DLAPH2, UBE4A, ACLY, NSD1, R3HDM1, CEP250, ATXN7L1, CD151, BLVRA, CCR2, INTS6L, MYO18A and RARA.

The present invention also discloses a detection kit for detecting excessive exposure of an individual to fine particulate matter PM2.5, wherein the genes identified by the biomarker primers further include: TMEM19, CLK4, MED15, UNK, ZNF280C, CEP170, ZBTB4, OLFM1, CDADC1, TFDP2, GAPT, CHD9 and SNX10.

The present invention discloses that the biological sample collected includes blood, plasma, serum, urine, feces, ascites, sputum, oral mucosal cells, gastric juice, bile, tissue, cells, organs, body fluids or any combination thereof.

In a preferred embodiment, the biological sample of the present invention is a blood sample.

The present invention discloses a method for determining a target gene, including polymerase chain reaction, real-time polymerase chain reaction, quantitative real-time reverse transcription polymerase chain reaction, droplet digital polymerase chain reaction, nested polymerase chain reaction, whole genome sequencing, enzyme-linked immunosorbent assay, Western blot, enzyme immunoassay, lateral flow immunochromatography or flow cytometer.

Among them, genome sequencing includes DNA whole genome sequencing or RNA whole genome sequencing.

In a preferred embodiment, the gene expression analysis method of the present invention is a quantitative real-time reverse transcription polymerase chain reaction.

The present invention discloses a method for evaluating whether an individual suffers from cancer caused by fine suspended particulate matter PM2.5, comprising at least the following steps: (a) providing a sample obtained from the individual; (b) determining the gene expression level of at least one target gene in the sample, wherein the at least one target gene includes at least one of the following: OXR1, PRPF38B, ITGAM, PPP2R1B and FAM102B; and (c) comparing the gene expression level of the at least one target gene in step (b) with that of a control group, wherein when the gene expression level of the OXR1, or the PRPF38B, or the ITGAM, or the PPP2R1B, or the FAM102B is higher than that of the control group, it is evaluated that the individual suffers from cancer caused by fine suspended particulate matter PM2.5.

The present invention discloses a method for evaluating whether an individual suffers from cancer caused by fine suspended particulate matter PM2.5, wherein the at least one target gene further comprises: PHF8, DYRK1B, ZKSCAN5, DIAPH2, UBE4A, ACLY, NSD1, R3HDM1, CEP250, ATXN7L1, CD151, BLVRA, CCR2, INTS6L, MYO18A and RARA, wherein when the PHF8 or the DYRK1B When the expression level of the gene of , or the gene of ZKSCAN5, or the gene of DIAPH2, or the gene of UBE4A, or the gene of ACLY, or the gene of NSD1, or the gene of R3HDM1 is lower than that of the control group, or the expression level of the gene of CEP250, or the gene of ATXN7L1, or the gene of CD151, or the gene of BLVRA, or the gene of CCR2, or the gene of INTS6L, or the gene of MYO18A, or the gene of RARA is higher than that of the control group, the individual is assessed to be suffering from cancer caused by fine suspended particulate matter PM2.5.

The present invention discloses a method for evaluating whether an individual suffers from cancer caused by fine suspended particulate matter PM2.5, wherein the at least one target gene further comprises: TMEM19, CLK4, MED15, UNK, ZNF280C, CEP170, ZBTB4, OLFM1, CDADC1, TFDP2, GAPT, CHD9 and SNX10. When the expression level of the TMEM19, or the CLK4, or the MED15, or the UNK, or the ZNF280C, or the CEP170, or the ZBTB4 gene is lower than that of the control group, or when the expression level of the OLFM1, or the CDADC1, or the TFDP2, or the GAPT, or the CHD9, or the SNX10 gene is higher than that of the control group, the individual is evaluated and judged to suffer from cancer caused by fine suspended particulate matter PM2.5.

The present invention discloses a method for evaluating whether an individual suffers from cognitive impairment caused by fine suspended particulate matter PM2.5, comprising at least the following steps: (a) providing a sample obtained from the individual; (b) determining the gene expression level of at least one target gene in the sample, wherein the at least one target gene comprises at least one of the following: OXR1, PRPF38B, ITGAM, PPP2R1B and FAM102B; and (c) comparing the gene expression level of the at least one target gene in step (b) with that of a control group, wherein when the gene expression level of the OXR1, or the PRPF38B, or the ITGAM, or the PRPF38B, or the FAM102B is higher than that of the control group, it is evaluated that the individual suffers from cognitive impairment caused by fine suspended particulate matter PM2.5.

The present invention discloses a method for evaluating whether an individual suffers from cognitive impairment caused by fine suspended particulate matter PM2.5, wherein the at least one target gene further comprises: PHF8, DYRK1B, ZKSCAN5, DIAPH2, UBE4A, ACLY, NSD1, R3HDM1, CEP250, ATXN7L1, CD151, BLVRA, CCR2, INTS6L, MYO18A and RARA, wherein when the PHF8, or the DYRK1B, When the expression level of the ZKSCAN5, DIAPH2, UBE4A, ACLY, NSD1, or R3HDM1 gene is lower than that of the control group, or when the expression level of the CEP250, ATXN7L1, CD151, BLVRA, CCR2, or INTS6L, MYO18A, or RARA gene is higher than that of the control group, the individual is assessed to suffer from cognitive impairment caused by fine suspended particulate matter PM2.5.

The present invention discloses a method for assessing whether an individual suffers from cognitive impairment caused by fine suspended particulate matter PM2.5, wherein the at least one target gene further comprises: TMEM19, CLK4, MED15, UNK, ZNF280C, CEP170, ZBTB4, OLFM1, CDADC1, TFDP2, GAPT, CHD9 and SNX10. When the expression level of the TMEM19, CLK4, MED15, UNK, ZNF280C, CEP170, or ZBTB4 gene is lower than that of the control group, or when the expression level of the OLFM1, CDADC1, TFDP2, GAPT, CHD9, or SNX10 gene is higher than that of the control group, it is assessed that the individual suffers from cognitive impairment caused by fine suspended particulate matter PM2.5.

The present invention discloses a method for evaluating whether an individual suffers from an autoimmune disease caused by fine suspended particulate matter PM2.5, comprising at least the following steps: (a) providing a sample obtained from the individual; (b) determining the gene expression level of at least one target gene in the sample, wherein the at least one target gene comprises at least one of the following: OXR1, PRPF38B, ITGAM, PPP2R1B and FAM102B; and (c) comparing the gene expression level of the at least one target gene in step (b) with that of a control group, wherein when the gene expression level of the OXR1, or the PRPF38B, or the ITGAM, or the PPP2R1B, or the FAM102B is higher than that of the control group, it is evaluated that the individual suffers from an autoimmune disease caused by fine suspended particulate matter PM2.5.

The present invention discloses a method for evaluating whether an individual suffers from an autoimmune disease caused by fine suspended particulate matter PM2.5, wherein the at least one target gene further comprises: PHF8, DYRK1B, ZKSCAN5, DIAPH2, UBE4A, ACLY, NSD1, R3HDM1, CEP250, ATXN7L1, CD151, BLVRA, CCR2, INTS6L, MYO18A and RARA, wherein when the PHF8 or the DYRK1B When the expression level of the gene of , or the gene of ZKSCAN5, or the gene of DIAPH2, or the gene of UBE4A, or the gene of ACLY, or the gene of NSD1, or the gene of R3HDM1 is lower than that of the control group, or the gene of CEP250, or the gene of ATXN7L1, or the gene of CD151, or the gene of BLVRA, or the gene of CCR2, or the gene of INTS6L, or the gene of MYO18A, or the gene of RARA is higher than that of the control group, the individual is assessed to suffer from an autoimmune disease caused by fine suspended particulate matter PM2.5.

The present invention discloses a method for evaluating whether an individual suffers from an autoimmune disease caused by fine suspended particulate matter PM2.5, wherein the at least one target gene further comprises: TMEM19, CLK4, MED15, UNK, ZNF280C, CEP170, ZBTB4, OLFM1, CDADC1, TFDP2, GAPT, CHD9 and SNX10. When the expression level of the TMEM19, or the CLK4, or the MED15, or the UNK, or the ZNF280C, or the CEP170, or the ZBTB4 gene is lower than that of the control group, or when the expression level of the OLFM1, or the CDADC1, or the TFDP2, or the GAPT, or the CHD9, or the SNX10 gene is higher than that of the control group, the individual is evaluated and judged to suffer from an autoimmune disease caused by fine suspended particulate matter PM2.5.

The above detailed description is a specific description of the feasible embodiments of the present invention, but the embodiments are not intended to limit the patent scope of the present invention. Any equivalent implementation or modification that does not deviate from the technical spirit of the present invention should be included in the patent scope of the present invention.

TWI857353B_111136370_SEQL.xml

Claims (4)

A method for assessing whether an individual is overexposed to fine particulate matter PM2.5 comprises at least the following steps: (a) providing a sample obtained from the subject; (b) determining the gene expression level of at least one target gene in the sample, wherein the at least one target gene comprises at least one of the following: PRPF38B, ITGAM, PPP2R1B and FAM102B; and (c) comparing the gene expression level of the at least one target gene in step (b) with that of a control group, wherein when the gene expression level of the PRPF38B, or the ITGAM, or the PPP2R1B, or the FAM102B is higher than that of the control group, it is assessed that the individual is overexposed to fine particulate matter PM2.5. The method of claim 1, wherein the at least one target gene further comprises: OXR1, PHF8, DYRK1B, ZKSCAN5, DIAPH2, UBE4A, ACLY, NSD1, R3HDM1, CEP250, ATXN7L1, CD151, BLVRA, CCR2, INTS6L, MYO18A and RARA, wherein when the PHF8, or the DYRK1B, or the ZKSCAN5 When the expression level of the DIAPH2, UBE4A, ACLY, NSD1, or R3HDM1 gene is lower than that of the control group, or when the expression level of the OXR1, CEP250, ATXN7L1, CD151, BLVRA, CCR2, INTS6L, MYO18A, or RARA gene is higher than that of the control group, the individual is assessed to be overexposed to fine particulate matter PM2.5. The method as described in claim 2, wherein the at least one target gene further comprises: TMEM19, CLK4, MED15, UNK, ZNF280C, CEP170, ZBTB4, OLFM1, CDADC1, TFDP2, GAPT, CHD9 and SNX10, wherein when the expression level of the TMEM19, or the CLK4, or the MED15, or the UNK, or the ZNF280C, or the CEP170, or the ZBTB4 gene is lower than that of the control group, or when the expression level of the OLFM1, or the CDADC1, or the TFDP2, or the GAPT, or the CHD9, or the SNX10 gene is higher than that of the control group, the individual is assessed to be overexposed to fine suspended particulate matter PM2.5. The method as described in claim 1, wherein the method for determining the gene expression level of the at least one target gene comprises polymerase chain reaction, real-time polymerase chain reaction, quantitative real-time reverse transcription polymerase chain reaction, droplet digital polymerase chain reaction, nested polymerase chain reaction, whole genome sequencing, enzyme-linked immunosorbent assay, Western blot, enzyme immunoassay, lateral flow immunochromatography or flow cytometer.

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