Emerging Methods and Resources for Biological Interrogation of Neuropsychiatric Polygenic Signal
Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Uffelmann, Emil [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021transfer abstract |
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| Schlagwörter: |
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| Umfang: |
13 |
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| Übergeordnetes Werk: |
Enthalten in: Iptakalim induces mitochondria-dependent apoptosis in hypoxic rat pulmonary arterial smooth muscle cells - Xu, Qi ELSEVIER, 2016, a journal of psychiatric neuroscience : a publication of the Society of Biological Psychiatry, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:89 ; year:2021 ; number:1 ; day:1 ; month:01 ; pages:41-53 ; extent:13 |
| Links: |
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| DOI / URN: |
10.1016/j.biopsych.2020.05.022 |
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| 520 | |a Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them. | ||
| 520 | |a Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them. | ||
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10.1016/j.biopsych.2020.05.022 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001219.pica (DE-627)ELV05224265X (ELSEVIER)S0006-3223(20)31628-0 DE-627 ger DE-627 rakwb eng 610 VZ 44.40 bkl Uffelmann, Emil verfasserin aut Emerging Methods and Resources for Biological Interrogation of Neuropsychiatric Polygenic Signal 2021transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them. Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them. Pathway analysis Elsevier molQTL Elsevier Gene-set analysis Elsevier Genome-wide association study Elsevier Polygenicity Elsevier Functional genomics Elsevier Posthuma, Danielle oth Enthalten in Elsevier Science Xu, Qi ELSEVIER Iptakalim induces mitochondria-dependent apoptosis in hypoxic rat pulmonary arterial smooth muscle cells 2016 a journal of psychiatric neuroscience : a publication of the Society of Biological Psychiatry Amsterdam [u.a.] (DE-627)ELV01006897X volume:89 year:2021 number:1 day:1 month:01 pages:41-53 extent:13 https://doi.org/10.1016/j.biopsych.2020.05.022 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 89 2021 1 1 0101 41-53 13 |
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10.1016/j.biopsych.2020.05.022 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001219.pica (DE-627)ELV05224265X (ELSEVIER)S0006-3223(20)31628-0 DE-627 ger DE-627 rakwb eng 610 VZ 44.40 bkl Uffelmann, Emil verfasserin aut Emerging Methods and Resources for Biological Interrogation of Neuropsychiatric Polygenic Signal 2021transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them. Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them. Pathway analysis Elsevier molQTL Elsevier Gene-set analysis Elsevier Genome-wide association study Elsevier Polygenicity Elsevier Functional genomics Elsevier Posthuma, Danielle oth Enthalten in Elsevier Science Xu, Qi ELSEVIER Iptakalim induces mitochondria-dependent apoptosis in hypoxic rat pulmonary arterial smooth muscle cells 2016 a journal of psychiatric neuroscience : a publication of the Society of Biological Psychiatry Amsterdam [u.a.] (DE-627)ELV01006897X volume:89 year:2021 number:1 day:1 month:01 pages:41-53 extent:13 https://doi.org/10.1016/j.biopsych.2020.05.022 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 89 2021 1 1 0101 41-53 13 |
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10.1016/j.biopsych.2020.05.022 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001219.pica (DE-627)ELV05224265X (ELSEVIER)S0006-3223(20)31628-0 DE-627 ger DE-627 rakwb eng 610 VZ 44.40 bkl Uffelmann, Emil verfasserin aut Emerging Methods and Resources for Biological Interrogation of Neuropsychiatric Polygenic Signal 2021transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them. Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them. Pathway analysis Elsevier molQTL Elsevier Gene-set analysis Elsevier Genome-wide association study Elsevier Polygenicity Elsevier Functional genomics Elsevier Posthuma, Danielle oth Enthalten in Elsevier Science Xu, Qi ELSEVIER Iptakalim induces mitochondria-dependent apoptosis in hypoxic rat pulmonary arterial smooth muscle cells 2016 a journal of psychiatric neuroscience : a publication of the Society of Biological Psychiatry Amsterdam [u.a.] (DE-627)ELV01006897X volume:89 year:2021 number:1 day:1 month:01 pages:41-53 extent:13 https://doi.org/10.1016/j.biopsych.2020.05.022 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 89 2021 1 1 0101 41-53 13 |
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10.1016/j.biopsych.2020.05.022 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001219.pica (DE-627)ELV05224265X (ELSEVIER)S0006-3223(20)31628-0 DE-627 ger DE-627 rakwb eng 610 VZ 44.40 bkl Uffelmann, Emil verfasserin aut Emerging Methods and Resources for Biological Interrogation of Neuropsychiatric Polygenic Signal 2021transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them. Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them. Pathway analysis Elsevier molQTL Elsevier Gene-set analysis Elsevier Genome-wide association study Elsevier Polygenicity Elsevier Functional genomics Elsevier Posthuma, Danielle oth Enthalten in Elsevier Science Xu, Qi ELSEVIER Iptakalim induces mitochondria-dependent apoptosis in hypoxic rat pulmonary arterial smooth muscle cells 2016 a journal of psychiatric neuroscience : a publication of the Society of Biological Psychiatry Amsterdam [u.a.] (DE-627)ELV01006897X volume:89 year:2021 number:1 day:1 month:01 pages:41-53 extent:13 https://doi.org/10.1016/j.biopsych.2020.05.022 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 89 2021 1 1 0101 41-53 13 |
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10.1016/j.biopsych.2020.05.022 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001219.pica (DE-627)ELV05224265X (ELSEVIER)S0006-3223(20)31628-0 DE-627 ger DE-627 rakwb eng 610 VZ 44.40 bkl Uffelmann, Emil verfasserin aut Emerging Methods and Resources for Biological Interrogation of Neuropsychiatric Polygenic Signal 2021transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them. Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them. Pathway analysis Elsevier molQTL Elsevier Gene-set analysis Elsevier Genome-wide association study Elsevier Polygenicity Elsevier Functional genomics Elsevier Posthuma, Danielle oth Enthalten in Elsevier Science Xu, Qi ELSEVIER Iptakalim induces mitochondria-dependent apoptosis in hypoxic rat pulmonary arterial smooth muscle cells 2016 a journal of psychiatric neuroscience : a publication of the Society of Biological Psychiatry Amsterdam [u.a.] (DE-627)ELV01006897X volume:89 year:2021 number:1 day:1 month:01 pages:41-53 extent:13 https://doi.org/10.1016/j.biopsych.2020.05.022 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 89 2021 1 1 0101 41-53 13 |
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Enthalten in Iptakalim induces mitochondria-dependent apoptosis in hypoxic rat pulmonary arterial smooth muscle cells Amsterdam [u.a.] volume:89 year:2021 number:1 day:1 month:01 pages:41-53 extent:13 |
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Iptakalim induces mitochondria-dependent apoptosis in hypoxic rat pulmonary arterial smooth muscle cells |
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emerging methods and resources for biological interrogation of neuropsychiatric polygenic signal |
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Emerging Methods and Resources for Biological Interrogation of Neuropsychiatric Polygenic Signal |
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Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them. |
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Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them. |
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Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them. |
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