209
T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains a...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ren, Min [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013transfer abstract |
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| Übergeordnetes Werk: |
Enthalten in: The minimal clinically important differences of the Simple Shoulder Test are different for different arthroplasty types - McLaughlin, Richard J. ELSEVIER, 2022, the official journal of the International Cytokine Society, Oxford [u.a.] |
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| Übergeordnetes Werk: |
volume:63 ; year:2013 ; number:3 ; pages:292 |
| Links: |
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| DOI / URN: |
10.1016/j.cyto.2013.06.212 |
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ELV022163220 |
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| 520 | |a T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains as well. To investigate the genetic factors that contribute to such differential immune responses, we have integrated computational genetic analysis and transcriptomic data to identify novel elements involved in Th1 differentiation. We determined the phenotypic profiles of in vitro differentiated Th1 cells from 16 inbred mouse strains by measuring the RNA and protein level of the Th1 signature cytokine (IFN©) at six time points. Then, according to the phenotypic ranking of 16 inbred strains, we performed a haplotype-based computational genetic analysis. At all time points, we observed strong and significant inter-strain differences, which suggested that the observed variations were due to genetic differences, and we identified ∼1075 genes (p <0.001) with polymorphisms that potentially contribute to the quantitative difference in IFN© expression. Many well known Th1 associated genes were found in this pool, including IFN© receptor, JAK2, STAT1, STAT4 and IRF4. We also established the transcriptomic profiles of Th1 cells from 4 mice strains by RNAseq analysis. As compared to naive CD4+ T cells, ∼80 genes had a significantly change in expression (FC>2, P <1e−10) in differentiated Th1 cells and had similar expression patterns to that of IFN© in the 4 mice strains, whereas ∼50 genes showed a pattern opposite to that of IFN©. After combining these results with SNP data, we are now evaluating candidate genes for novel roles in regulating IFNγ expression upon Th1 differentiation. | ||
| 520 | |a T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains as well. To investigate the genetic factors that contribute to such differential immune responses, we have integrated computational genetic analysis and transcriptomic data to identify novel elements involved in Th1 differentiation. We determined the phenotypic profiles of in vitro differentiated Th1 cells from 16 inbred mouse strains by measuring the RNA and protein level of the Th1 signature cytokine (IFN©) at six time points. Then, according to the phenotypic ranking of 16 inbred strains, we performed a haplotype-based computational genetic analysis. At all time points, we observed strong and significant inter-strain differences, which suggested that the observed variations were due to genetic differences, and we identified ∼1075 genes (p <0.001) with polymorphisms that potentially contribute to the quantitative difference in IFN© expression. Many well known Th1 associated genes were found in this pool, including IFN© receptor, JAK2, STAT1, STAT4 and IRF4. We also established the transcriptomic profiles of Th1 cells from 4 mice strains by RNAseq analysis. As compared to naive CD4+ T cells, ∼80 genes had a significantly change in expression (FC>2, P <1e−10) in differentiated Th1 cells and had similar expression patterns to that of IFN© in the 4 mice strains, whereas ∼50 genes showed a pattern opposite to that of IFN©. After combining these results with SNP data, we are now evaluating candidate genes for novel roles in regulating IFNγ expression upon Th1 differentiation. | ||
| 700 | 1 | |a Li, Peng |4 oth | |
| 700 | 1 | |a Zheng, Ming |4 oth | |
| 700 | 1 | |a Peltz, Gary |4 oth | |
| 700 | 1 | |a Leonard, Warren J. |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier |a McLaughlin, Richard J. ELSEVIER |t The minimal clinically important differences of the Simple Shoulder Test are different for different arthroplasty types |d 2022 |d the official journal of the International Cytokine Society |g Oxford [u.a.] |w (DE-627)ELV008219540 |
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10.1016/j.cyto.2013.06.212 doi GBVA2013017000028.pica (DE-627)ELV022163220 (ELSEVIER)S1043-4666(13)00486-9 DE-627 ger DE-627 rakwb eng 570 570 DE-600 610 VZ 44.83 bkl Ren, Min verfasserin aut 209 2013transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains as well. To investigate the genetic factors that contribute to such differential immune responses, we have integrated computational genetic analysis and transcriptomic data to identify novel elements involved in Th1 differentiation. We determined the phenotypic profiles of in vitro differentiated Th1 cells from 16 inbred mouse strains by measuring the RNA and protein level of the Th1 signature cytokine (IFN©) at six time points. Then, according to the phenotypic ranking of 16 inbred strains, we performed a haplotype-based computational genetic analysis. At all time points, we observed strong and significant inter-strain differences, which suggested that the observed variations were due to genetic differences, and we identified ∼1075 genes (p <0.001) with polymorphisms that potentially contribute to the quantitative difference in IFN© expression. Many well known Th1 associated genes were found in this pool, including IFN© receptor, JAK2, STAT1, STAT4 and IRF4. We also established the transcriptomic profiles of Th1 cells from 4 mice strains by RNAseq analysis. As compared to naive CD4+ T cells, ∼80 genes had a significantly change in expression (FC>2, P <1e−10) in differentiated Th1 cells and had similar expression patterns to that of IFN© in the 4 mice strains, whereas ∼50 genes showed a pattern opposite to that of IFN©. After combining these results with SNP data, we are now evaluating candidate genes for novel roles in regulating IFNγ expression upon Th1 differentiation. T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains as well. To investigate the genetic factors that contribute to such differential immune responses, we have integrated computational genetic analysis and transcriptomic data to identify novel elements involved in Th1 differentiation. We determined the phenotypic profiles of in vitro differentiated Th1 cells from 16 inbred mouse strains by measuring the RNA and protein level of the Th1 signature cytokine (IFN©) at six time points. Then, according to the phenotypic ranking of 16 inbred strains, we performed a haplotype-based computational genetic analysis. At all time points, we observed strong and significant inter-strain differences, which suggested that the observed variations were due to genetic differences, and we identified ∼1075 genes (p <0.001) with polymorphisms that potentially contribute to the quantitative difference in IFN© expression. Many well known Th1 associated genes were found in this pool, including IFN© receptor, JAK2, STAT1, STAT4 and IRF4. We also established the transcriptomic profiles of Th1 cells from 4 mice strains by RNAseq analysis. As compared to naive CD4+ T cells, ∼80 genes had a significantly change in expression (FC>2, P <1e−10) in differentiated Th1 cells and had similar expression patterns to that of IFN© in the 4 mice strains, whereas ∼50 genes showed a pattern opposite to that of IFN©. After combining these results with SNP data, we are now evaluating candidate genes for novel roles in regulating IFNγ expression upon Th1 differentiation. Li, Peng oth Zheng, Ming oth Peltz, Gary oth Leonard, Warren J. oth Enthalten in Elsevier McLaughlin, Richard J. ELSEVIER The minimal clinically important differences of the Simple Shoulder Test are different for different arthroplasty types 2022 the official journal of the International Cytokine Society Oxford [u.a.] (DE-627)ELV008219540 volume:63 year:2013 number:3 pages:292 https://doi.org/10.1016/j.cyto.2013.06.212 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.83 Rheumatologie Orthopädie VZ AR 63 2013 3 292 045F 570 |
| spelling |
10.1016/j.cyto.2013.06.212 doi GBVA2013017000028.pica (DE-627)ELV022163220 (ELSEVIER)S1043-4666(13)00486-9 DE-627 ger DE-627 rakwb eng 570 570 DE-600 610 VZ 44.83 bkl Ren, Min verfasserin aut 209 2013transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains as well. To investigate the genetic factors that contribute to such differential immune responses, we have integrated computational genetic analysis and transcriptomic data to identify novel elements involved in Th1 differentiation. We determined the phenotypic profiles of in vitro differentiated Th1 cells from 16 inbred mouse strains by measuring the RNA and protein level of the Th1 signature cytokine (IFN©) at six time points. Then, according to the phenotypic ranking of 16 inbred strains, we performed a haplotype-based computational genetic analysis. At all time points, we observed strong and significant inter-strain differences, which suggested that the observed variations were due to genetic differences, and we identified ∼1075 genes (p <0.001) with polymorphisms that potentially contribute to the quantitative difference in IFN© expression. Many well known Th1 associated genes were found in this pool, including IFN© receptor, JAK2, STAT1, STAT4 and IRF4. We also established the transcriptomic profiles of Th1 cells from 4 mice strains by RNAseq analysis. As compared to naive CD4+ T cells, ∼80 genes had a significantly change in expression (FC>2, P <1e−10) in differentiated Th1 cells and had similar expression patterns to that of IFN© in the 4 mice strains, whereas ∼50 genes showed a pattern opposite to that of IFN©. After combining these results with SNP data, we are now evaluating candidate genes for novel roles in regulating IFNγ expression upon Th1 differentiation. T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains as well. To investigate the genetic factors that contribute to such differential immune responses, we have integrated computational genetic analysis and transcriptomic data to identify novel elements involved in Th1 differentiation. We determined the phenotypic profiles of in vitro differentiated Th1 cells from 16 inbred mouse strains by measuring the RNA and protein level of the Th1 signature cytokine (IFN©) at six time points. Then, according to the phenotypic ranking of 16 inbred strains, we performed a haplotype-based computational genetic analysis. At all time points, we observed strong and significant inter-strain differences, which suggested that the observed variations were due to genetic differences, and we identified ∼1075 genes (p <0.001) with polymorphisms that potentially contribute to the quantitative difference in IFN© expression. Many well known Th1 associated genes were found in this pool, including IFN© receptor, JAK2, STAT1, STAT4 and IRF4. We also established the transcriptomic profiles of Th1 cells from 4 mice strains by RNAseq analysis. As compared to naive CD4+ T cells, ∼80 genes had a significantly change in expression (FC>2, P <1e−10) in differentiated Th1 cells and had similar expression patterns to that of IFN© in the 4 mice strains, whereas ∼50 genes showed a pattern opposite to that of IFN©. After combining these results with SNP data, we are now evaluating candidate genes for novel roles in regulating IFNγ expression upon Th1 differentiation. Li, Peng oth Zheng, Ming oth Peltz, Gary oth Leonard, Warren J. oth Enthalten in Elsevier McLaughlin, Richard J. ELSEVIER The minimal clinically important differences of the Simple Shoulder Test are different for different arthroplasty types 2022 the official journal of the International Cytokine Society Oxford [u.a.] (DE-627)ELV008219540 volume:63 year:2013 number:3 pages:292 https://doi.org/10.1016/j.cyto.2013.06.212 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.83 Rheumatologie Orthopädie VZ AR 63 2013 3 292 045F 570 |
| allfields_unstemmed |
10.1016/j.cyto.2013.06.212 doi GBVA2013017000028.pica (DE-627)ELV022163220 (ELSEVIER)S1043-4666(13)00486-9 DE-627 ger DE-627 rakwb eng 570 570 DE-600 610 VZ 44.83 bkl Ren, Min verfasserin aut 209 2013transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains as well. To investigate the genetic factors that contribute to such differential immune responses, we have integrated computational genetic analysis and transcriptomic data to identify novel elements involved in Th1 differentiation. We determined the phenotypic profiles of in vitro differentiated Th1 cells from 16 inbred mouse strains by measuring the RNA and protein level of the Th1 signature cytokine (IFN©) at six time points. Then, according to the phenotypic ranking of 16 inbred strains, we performed a haplotype-based computational genetic analysis. At all time points, we observed strong and significant inter-strain differences, which suggested that the observed variations were due to genetic differences, and we identified ∼1075 genes (p <0.001) with polymorphisms that potentially contribute to the quantitative difference in IFN© expression. Many well known Th1 associated genes were found in this pool, including IFN© receptor, JAK2, STAT1, STAT4 and IRF4. We also established the transcriptomic profiles of Th1 cells from 4 mice strains by RNAseq analysis. As compared to naive CD4+ T cells, ∼80 genes had a significantly change in expression (FC>2, P <1e−10) in differentiated Th1 cells and had similar expression patterns to that of IFN© in the 4 mice strains, whereas ∼50 genes showed a pattern opposite to that of IFN©. After combining these results with SNP data, we are now evaluating candidate genes for novel roles in regulating IFNγ expression upon Th1 differentiation. T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains as well. To investigate the genetic factors that contribute to such differential immune responses, we have integrated computational genetic analysis and transcriptomic data to identify novel elements involved in Th1 differentiation. We determined the phenotypic profiles of in vitro differentiated Th1 cells from 16 inbred mouse strains by measuring the RNA and protein level of the Th1 signature cytokine (IFN©) at six time points. Then, according to the phenotypic ranking of 16 inbred strains, we performed a haplotype-based computational genetic analysis. At all time points, we observed strong and significant inter-strain differences, which suggested that the observed variations were due to genetic differences, and we identified ∼1075 genes (p <0.001) with polymorphisms that potentially contribute to the quantitative difference in IFN© expression. Many well known Th1 associated genes were found in this pool, including IFN© receptor, JAK2, STAT1, STAT4 and IRF4. We also established the transcriptomic profiles of Th1 cells from 4 mice strains by RNAseq analysis. As compared to naive CD4+ T cells, ∼80 genes had a significantly change in expression (FC>2, P <1e−10) in differentiated Th1 cells and had similar expression patterns to that of IFN© in the 4 mice strains, whereas ∼50 genes showed a pattern opposite to that of IFN©. After combining these results with SNP data, we are now evaluating candidate genes for novel roles in regulating IFNγ expression upon Th1 differentiation. Li, Peng oth Zheng, Ming oth Peltz, Gary oth Leonard, Warren J. oth Enthalten in Elsevier McLaughlin, Richard J. ELSEVIER The minimal clinically important differences of the Simple Shoulder Test are different for different arthroplasty types 2022 the official journal of the International Cytokine Society Oxford [u.a.] (DE-627)ELV008219540 volume:63 year:2013 number:3 pages:292 https://doi.org/10.1016/j.cyto.2013.06.212 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.83 Rheumatologie Orthopädie VZ AR 63 2013 3 292 045F 570 |
| allfieldsGer |
10.1016/j.cyto.2013.06.212 doi GBVA2013017000028.pica (DE-627)ELV022163220 (ELSEVIER)S1043-4666(13)00486-9 DE-627 ger DE-627 rakwb eng 570 570 DE-600 610 VZ 44.83 bkl Ren, Min verfasserin aut 209 2013transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains as well. To investigate the genetic factors that contribute to such differential immune responses, we have integrated computational genetic analysis and transcriptomic data to identify novel elements involved in Th1 differentiation. We determined the phenotypic profiles of in vitro differentiated Th1 cells from 16 inbred mouse strains by measuring the RNA and protein level of the Th1 signature cytokine (IFN©) at six time points. Then, according to the phenotypic ranking of 16 inbred strains, we performed a haplotype-based computational genetic analysis. At all time points, we observed strong and significant inter-strain differences, which suggested that the observed variations were due to genetic differences, and we identified ∼1075 genes (p <0.001) with polymorphisms that potentially contribute to the quantitative difference in IFN© expression. Many well known Th1 associated genes were found in this pool, including IFN© receptor, JAK2, STAT1, STAT4 and IRF4. We also established the transcriptomic profiles of Th1 cells from 4 mice strains by RNAseq analysis. As compared to naive CD4+ T cells, ∼80 genes had a significantly change in expression (FC>2, P <1e−10) in differentiated Th1 cells and had similar expression patterns to that of IFN© in the 4 mice strains, whereas ∼50 genes showed a pattern opposite to that of IFN©. After combining these results with SNP data, we are now evaluating candidate genes for novel roles in regulating IFNγ expression upon Th1 differentiation. T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains as well. To investigate the genetic factors that contribute to such differential immune responses, we have integrated computational genetic analysis and transcriptomic data to identify novel elements involved in Th1 differentiation. We determined the phenotypic profiles of in vitro differentiated Th1 cells from 16 inbred mouse strains by measuring the RNA and protein level of the Th1 signature cytokine (IFN©) at six time points. Then, according to the phenotypic ranking of 16 inbred strains, we performed a haplotype-based computational genetic analysis. At all time points, we observed strong and significant inter-strain differences, which suggested that the observed variations were due to genetic differences, and we identified ∼1075 genes (p <0.001) with polymorphisms that potentially contribute to the quantitative difference in IFN© expression. Many well known Th1 associated genes were found in this pool, including IFN© receptor, JAK2, STAT1, STAT4 and IRF4. We also established the transcriptomic profiles of Th1 cells from 4 mice strains by RNAseq analysis. As compared to naive CD4+ T cells, ∼80 genes had a significantly change in expression (FC>2, P <1e−10) in differentiated Th1 cells and had similar expression patterns to that of IFN© in the 4 mice strains, whereas ∼50 genes showed a pattern opposite to that of IFN©. After combining these results with SNP data, we are now evaluating candidate genes for novel roles in regulating IFNγ expression upon Th1 differentiation. Li, Peng oth Zheng, Ming oth Peltz, Gary oth Leonard, Warren J. oth Enthalten in Elsevier McLaughlin, Richard J. ELSEVIER The minimal clinically important differences of the Simple Shoulder Test are different for different arthroplasty types 2022 the official journal of the International Cytokine Society Oxford [u.a.] (DE-627)ELV008219540 volume:63 year:2013 number:3 pages:292 https://doi.org/10.1016/j.cyto.2013.06.212 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.83 Rheumatologie Orthopädie VZ AR 63 2013 3 292 045F 570 |
| allfieldsSound |
10.1016/j.cyto.2013.06.212 doi GBVA2013017000028.pica (DE-627)ELV022163220 (ELSEVIER)S1043-4666(13)00486-9 DE-627 ger DE-627 rakwb eng 570 570 DE-600 610 VZ 44.83 bkl Ren, Min verfasserin aut 209 2013transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains as well. To investigate the genetic factors that contribute to such differential immune responses, we have integrated computational genetic analysis and transcriptomic data to identify novel elements involved in Th1 differentiation. We determined the phenotypic profiles of in vitro differentiated Th1 cells from 16 inbred mouse strains by measuring the RNA and protein level of the Th1 signature cytokine (IFN©) at six time points. Then, according to the phenotypic ranking of 16 inbred strains, we performed a haplotype-based computational genetic analysis. At all time points, we observed strong and significant inter-strain differences, which suggested that the observed variations were due to genetic differences, and we identified ∼1075 genes (p <0.001) with polymorphisms that potentially contribute to the quantitative difference in IFN© expression. Many well known Th1 associated genes were found in this pool, including IFN© receptor, JAK2, STAT1, STAT4 and IRF4. We also established the transcriptomic profiles of Th1 cells from 4 mice strains by RNAseq analysis. As compared to naive CD4+ T cells, ∼80 genes had a significantly change in expression (FC>2, P <1e−10) in differentiated Th1 cells and had similar expression patterns to that of IFN© in the 4 mice strains, whereas ∼50 genes showed a pattern opposite to that of IFN©. After combining these results with SNP data, we are now evaluating candidate genes for novel roles in regulating IFNγ expression upon Th1 differentiation. T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains as well. To investigate the genetic factors that contribute to such differential immune responses, we have integrated computational genetic analysis and transcriptomic data to identify novel elements involved in Th1 differentiation. We determined the phenotypic profiles of in vitro differentiated Th1 cells from 16 inbred mouse strains by measuring the RNA and protein level of the Th1 signature cytokine (IFN©) at six time points. Then, according to the phenotypic ranking of 16 inbred strains, we performed a haplotype-based computational genetic analysis. At all time points, we observed strong and significant inter-strain differences, which suggested that the observed variations were due to genetic differences, and we identified ∼1075 genes (p <0.001) with polymorphisms that potentially contribute to the quantitative difference in IFN© expression. Many well known Th1 associated genes were found in this pool, including IFN© receptor, JAK2, STAT1, STAT4 and IRF4. We also established the transcriptomic profiles of Th1 cells from 4 mice strains by RNAseq analysis. As compared to naive CD4+ T cells, ∼80 genes had a significantly change in expression (FC>2, P <1e−10) in differentiated Th1 cells and had similar expression patterns to that of IFN© in the 4 mice strains, whereas ∼50 genes showed a pattern opposite to that of IFN©. After combining these results with SNP data, we are now evaluating candidate genes for novel roles in regulating IFNγ expression upon Th1 differentiation. Li, Peng oth Zheng, Ming oth Peltz, Gary oth Leonard, Warren J. oth Enthalten in Elsevier McLaughlin, Richard J. ELSEVIER The minimal clinically important differences of the Simple Shoulder Test are different for different arthroplasty types 2022 the official journal of the International Cytokine Society Oxford [u.a.] (DE-627)ELV008219540 volume:63 year:2013 number:3 pages:292 https://doi.org/10.1016/j.cyto.2013.06.212 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.83 Rheumatologie Orthopädie VZ AR 63 2013 3 292 045F 570 |
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Enthalten in The minimal clinically important differences of the Simple Shoulder Test are different for different arthroplasty types Oxford [u.a.] volume:63 year:2013 number:3 pages:292 |
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Enthalten in The minimal clinically important differences of the Simple Shoulder Test are different for different arthroplasty types Oxford [u.a.] volume:63 year:2013 number:3 pages:292 |
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T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains as well. To investigate the genetic factors that contribute to such differential immune responses, we have integrated computational genetic analysis and transcriptomic data to identify novel elements involved in Th1 differentiation. We determined the phenotypic profiles of in vitro differentiated Th1 cells from 16 inbred mouse strains by measuring the RNA and protein level of the Th1 signature cytokine (IFN©) at six time points. Then, according to the phenotypic ranking of 16 inbred strains, we performed a haplotype-based computational genetic analysis. At all time points, we observed strong and significant inter-strain differences, which suggested that the observed variations were due to genetic differences, and we identified ∼1075 genes (p <0.001) with polymorphisms that potentially contribute to the quantitative difference in IFN© expression. Many well known Th1 associated genes were found in this pool, including IFN© receptor, JAK2, STAT1, STAT4 and IRF4. We also established the transcriptomic profiles of Th1 cells from 4 mice strains by RNAseq analysis. As compared to naive CD4+ T cells, ∼80 genes had a significantly change in expression (FC>2, P <1e−10) in differentiated Th1 cells and had similar expression patterns to that of IFN© in the 4 mice strains, whereas ∼50 genes showed a pattern opposite to that of IFN©. After combining these results with SNP data, we are now evaluating candidate genes for novel roles in regulating IFNγ expression upon Th1 differentiation. |
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T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains as well. To investigate the genetic factors that contribute to such differential immune responses, we have integrated computational genetic analysis and transcriptomic data to identify novel elements involved in Th1 differentiation. We determined the phenotypic profiles of in vitro differentiated Th1 cells from 16 inbred mouse strains by measuring the RNA and protein level of the Th1 signature cytokine (IFN©) at six time points. Then, according to the phenotypic ranking of 16 inbred strains, we performed a haplotype-based computational genetic analysis. At all time points, we observed strong and significant inter-strain differences, which suggested that the observed variations were due to genetic differences, and we identified ∼1075 genes (p <0.001) with polymorphisms that potentially contribute to the quantitative difference in IFN© expression. Many well known Th1 associated genes were found in this pool, including IFN© receptor, JAK2, STAT1, STAT4 and IRF4. We also established the transcriptomic profiles of Th1 cells from 4 mice strains by RNAseq analysis. As compared to naive CD4+ T cells, ∼80 genes had a significantly change in expression (FC>2, P <1e−10) in differentiated Th1 cells and had similar expression patterns to that of IFN© in the 4 mice strains, whereas ∼50 genes showed a pattern opposite to that of IFN©. After combining these results with SNP data, we are now evaluating candidate genes for novel roles in regulating IFNγ expression upon Th1 differentiation. |
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T helper (Th) cells play critical functions in response to infectious, allergic, and autoimmune diseases. Upon exposure to an infectious agent or stimulus, different types of Th responses are observed, which influence disease outcome, with differences in responses in different inbred mouse strains as well. To investigate the genetic factors that contribute to such differential immune responses, we have integrated computational genetic analysis and transcriptomic data to identify novel elements involved in Th1 differentiation. We determined the phenotypic profiles of in vitro differentiated Th1 cells from 16 inbred mouse strains by measuring the RNA and protein level of the Th1 signature cytokine (IFN©) at six time points. Then, according to the phenotypic ranking of 16 inbred strains, we performed a haplotype-based computational genetic analysis. At all time points, we observed strong and significant inter-strain differences, which suggested that the observed variations were due to genetic differences, and we identified ∼1075 genes (p <0.001) with polymorphisms that potentially contribute to the quantitative difference in IFN© expression. Many well known Th1 associated genes were found in this pool, including IFN© receptor, JAK2, STAT1, STAT4 and IRF4. We also established the transcriptomic profiles of Th1 cells from 4 mice strains by RNAseq analysis. As compared to naive CD4+ T cells, ∼80 genes had a significantly change in expression (FC>2, P <1e−10) in differentiated Th1 cells and had similar expression patterns to that of IFN© in the 4 mice strains, whereas ∼50 genes showed a pattern opposite to that of IFN©. After combining these results with SNP data, we are now evaluating candidate genes for novel roles in regulating IFNγ expression upon Th1 differentiation. |
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