Focus on Causality in ESC/iPSC-Based Modeling of Psychiatric Disorders
Genome-wide association studies (GWAS) have identified an increasing number of genetic variants that significantly associate with psychiatric disorders. Despite this wealth of information, our knowledge of which variants causally contribute to disease, how they interact, and even more so of the func...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-02-01
|
| Series: | Cells |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4409/9/2/366 |
| _version_ | 1827833945424658432 |
|---|---|
| author | Anke Hoffmann Michael Ziller Dietmar Spengler |
| author_facet | Anke Hoffmann Michael Ziller Dietmar Spengler |
| author_sort | Anke Hoffmann |
| collection | DOAJ |
| description | Genome-wide association studies (GWAS) have identified an increasing number of genetic variants that significantly associate with psychiatric disorders. Despite this wealth of information, our knowledge of which variants causally contribute to disease, how they interact, and even more so of the functions they regulate, is still poor. The availability of embryonic stem cells (ESCs) and the advent of patient-specific induced pluripotent stem cells (iPSCs) has opened new opportunities to investigate genetic risk variants in living disease-relevant cells. Here, we analyze how this progress has contributed to the analysis of causal relationships between genetic risk variants and neuronal phenotypes, especially in schizophrenia (SCZ) and bipolar disorder (BD). Studies on rare, highly penetrant risk variants have originally led the field, until more recently when the development of (epi-) genetic editing techniques spurred studies on cause-effect relationships between common low risk variants and their associated neuronal phenotypes. This reorientation not only offers new insights, but also raises issues on interpretability. Concluding, we consider potential caveats and upcoming developments in the field of ESC/iPSC-based modeling of causality in psychiatric disorders. |
| first_indexed | 2024-03-12T05:41:47Z |
| format | Article |
| id | doaj.art-9e7a49f2dd12421ea10dff3029ff87af |
| institution | Directory Open Access Journal |
| issn | 2073-4409 |
| language | English |
| last_indexed | 2024-03-12T05:41:47Z |
| publishDate | 2020-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cells |
| spelling | doaj.art-9e7a49f2dd12421ea10dff3029ff87af2023-09-03T06:01:57ZengMDPI AGCells2073-44092020-02-019236610.3390/cells9020366cells9020366Focus on Causality in ESC/iPSC-Based Modeling of Psychiatric DisordersAnke Hoffmann0Michael Ziller1Dietmar Spengler2Department of Translational Research in Psychiatry, Max-Planck Institute of Psychiatry, 80804 Munich, GermanyDepartment of Translational Research in Psychiatry, Max-Planck Institute of Psychiatry, 80804 Munich, GermanyDepartment of Translational Research in Psychiatry, Max-Planck Institute of Psychiatry, 80804 Munich, GermanyGenome-wide association studies (GWAS) have identified an increasing number of genetic variants that significantly associate with psychiatric disorders. Despite this wealth of information, our knowledge of which variants causally contribute to disease, how they interact, and even more so of the functions they regulate, is still poor. The availability of embryonic stem cells (ESCs) and the advent of patient-specific induced pluripotent stem cells (iPSCs) has opened new opportunities to investigate genetic risk variants in living disease-relevant cells. Here, we analyze how this progress has contributed to the analysis of causal relationships between genetic risk variants and neuronal phenotypes, especially in schizophrenia (SCZ) and bipolar disorder (BD). Studies on rare, highly penetrant risk variants have originally led the field, until more recently when the development of (epi-) genetic editing techniques spurred studies on cause-effect relationships between common low risk variants and their associated neuronal phenotypes. This reorientation not only offers new insights, but also raises issues on interpretability. Concluding, we consider potential caveats and upcoming developments in the field of ESC/iPSC-based modeling of causality in psychiatric disorders.https://www.mdpi.com/2073-4409/9/2/366patient-specific ipscsschizophreniabipolar disordercopy number variationcommon variation(epi-) genomic editingmassively parallel reporter assays |
| spellingShingle | Anke Hoffmann Michael Ziller Dietmar Spengler Focus on Causality in ESC/iPSC-Based Modeling of Psychiatric Disorders Cells patient-specific ipscs schizophrenia bipolar disorder copy number variation common variation (epi-) genomic editing massively parallel reporter assays |
| title | Focus on Causality in ESC/iPSC-Based Modeling of Psychiatric Disorders |
| title_full | Focus on Causality in ESC/iPSC-Based Modeling of Psychiatric Disorders |
| title_fullStr | Focus on Causality in ESC/iPSC-Based Modeling of Psychiatric Disorders |
| title_full_unstemmed | Focus on Causality in ESC/iPSC-Based Modeling of Psychiatric Disorders |
| title_short | Focus on Causality in ESC/iPSC-Based Modeling of Psychiatric Disorders |
| title_sort | focus on causality in esc ipsc based modeling of psychiatric disorders |
| topic | patient-specific ipscs schizophrenia bipolar disorder copy number variation common variation (epi-) genomic editing massively parallel reporter assays |
| url | https://www.mdpi.com/2073-4409/9/2/366 |
| work_keys_str_mv | AT ankehoffmann focusoncausalityinescipscbasedmodelingofpsychiatricdisorders AT michaelziller focusoncausalityinescipscbasedmodelingofpsychiatricdisorders AT dietmarspengler focusoncausalityinescipscbasedmodelingofpsychiatricdisorders |