|
|
| PMID |
|
|
| TITLE |
|
| Genomics-driven screening for causal determinants of suicide attempt. |
|
| ABSTRACT |
|
| OBJECTIVE |
NlmCategory: UNASSIGNED |
| Each year, around one million people die by suicide. Despite its recognition as a public health concern, large-scale research on causal determinants of suicide attempt risk is scarce. Here, we leverage results from a recent genome-wide association study (GWAS) of suicide attempt to perform a data-driven screening of traits causally associated with suicide attempt. |
| METHODS |
NlmCategory: UNASSIGNED |
| Each year, around one million people die by suicide. Despite its recognition as a public health concern, large-scale research on causal determinants of suicide attempt risk is scarce. Here, we leverage results from a recent genome-wide association study (GWAS) of suicide attempt to perform a data-driven screening of traits causally associated with suicide attempt. We performed a hypothesis-generating phenome-wide screening of causal relationships between suicide attempt risk and 1520 traits, which have been systematically aggregated on the Complex-Traits Genomics Virtual Lab platform. We employed the latent causal variable (LCV) method, which uses results from GWAS to assess whether a causal relationship can explain a genetic correlation between two traits. If a trait causally influences another one, the genetic variants that increase risk for the causal trait will also increase the risk for the outcome inducing a genetic correlation. Nonetheless, a genetic correlation can also be observed when traits share common pathways. The LCV method can assess whether the pattern of genetic effects for two genetically correlated traits support a causal association rather than a shared aetiology. |
| RESULTS |
NlmCategory: UNASSIGNED |
| Each year, around one million people die by suicide. Despite its recognition as a public health concern, large-scale research on causal determinants of suicide attempt risk is scarce. Here, we leverage results from a recent genome-wide association study (GWAS) of suicide attempt to perform a data-driven screening of traits causally associated with suicide attempt. We performed a hypothesis-generating phenome-wide screening of causal relationships between suicide attempt risk and 1520 traits, which have been systematically aggregated on the Complex-Traits Genomics Virtual Lab platform. We employed the latent causal variable (LCV) method, which uses results from GWAS to assess whether a causal relationship can explain a genetic correlation between two traits. If a trait causally influences another one, the genetic variants that increase risk for the causal trait will also increase the risk for the outcome inducing a genetic correlation. Nonetheless, a genetic correlation can also be observed when traits share common pathways. The LCV method can assess whether the pattern of genetic effects for two genetically correlated traits support a causal association rather than a shared aetiology. Our approach identified 62 traits that increased risk for suicide attempt. Risk factors identified can be broadly classified into (1) physical health disorders, including oesophagitis, fibromyalgia, hernia and cancer; (2) mental health-related traits, such as depression, substance use disorders and anxiety; and (3) lifestyle traits including being involved in combat or exposure to a war zone, and specific job categories such as being a truck driver or machine operator. |
| CONCLUSIONS |
NlmCategory: UNASSIGNED |
| Each year, around one million people die by suicide. Despite its recognition as a public health concern, large-scale research on causal determinants of suicide attempt risk is scarce. Here, we leverage results from a recent genome-wide association study (GWAS) of suicide attempt to perform a data-driven screening of traits causally associated with suicide attempt. We performed a hypothesis-generating phenome-wide screening of causal relationships between suicide attempt risk and 1520 traits, which have been systematically aggregated on the Complex-Traits Genomics Virtual Lab platform. We employed the latent causal variable (LCV) method, which uses results from GWAS to assess whether a causal relationship can explain a genetic correlation between two traits. If a trait causally influences another one, the genetic variants that increase risk for the causal trait will also increase the risk for the outcome inducing a genetic correlation. Nonetheless, a genetic correlation can also be observed when traits share common pathways. The LCV method can assess whether the pattern of genetic effects for two genetically correlated traits support a causal association rather than a shared aetiology. Our approach identified 62 traits that increased risk for suicide attempt. Risk factors identified can be broadly classified into (1) physical health disorders, including oesophagitis, fibromyalgia, hernia and cancer; (2) mental health-related traits, such as depression, substance use disorders and anxiety; and (3) lifestyle traits including being involved in combat or exposure to a war zone, and specific job categories such as being a truck driver or machine operator. Suicide attempt risk is likely explained by a combination of behavioural phenotypes and risk for both physical and psychiatric disorders. Our results also suggest that substance use behaviours and pain-related conditions are associated with an increased suicide attempt risk, elucidating important causal mechanisms that underpin this significant public health problem. |
|
| DATE PUBLISHED |
|
|
| HISTORY |
|
| PUBSTATUS |
PUBSTATUSDATE |
| entrez |
2022/04/11 08:43 |
| pubmed |
2022/04/12 06:00 |
| medline |
2022/04/12 06:00 |
|
| AUTHORS |
|
| NAME |
COLLECTIVENAME |
LASTNAME |
FORENAME |
INITIALS |
AFFILIATION |
AFFILIATIONINFO |
| Campos AI |
|
Campos |
Adrian I |
AI |
|
School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD Australia. |
| Garcia-Marin LM |
|
Garcia-Marin |
Luis M |
LM |
|
School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD Australia. |
| Christensen H |
|
Christensen |
Helen |
H |
|
Black Dog Institute, University of New South Wales, Sydney, NSW, Australia. |
| Batterham PJ |
|
Batterham |
Philip J |
PJ |
|
Centre for Mental Health Research, Research School of Population Health, Australian National University, Canberra, ACT, Australia. |
| van Velzen LS |
|
van Velzen |
Laura S |
LS |
|
Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia. |
| Schmaal L |
|
Schmaal |
Lianne |
L |
|
Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia. |
|
International Suicide Genetics Consortium |
|
|
|
|
|
| Rabinowitz JA |
|
Rabinowitz |
Jill A |
JA |
|
Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. |
| Jahanshad N |
|
Jahanshad |
Neda |
N |
|
Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina Del Rey, CA, USA. |
| Martin NG |
|
Martin |
Nicholas G |
NG |
|
Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia. |
| Cuellar-Partida G |
|
Cuellar-Partida |
Gabriel |
G |
|
Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia. |
| Ruderfer D |
|
Ruderfer |
Douglas |
D |
|
Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA. |
| Mullins N |
|
Mullins |
Niamh |
N |
|
Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA. |
| Rentería ME |
|
Rentería |
Miguel E |
ME |
|
School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD Australia. |
|
| INVESTIGATORS |
|
|
| JOURNAL |
|
| VOLUME: |
| ISSUE: |
| TITLE: The Australian and New Zealand journal of psychiatry |
| ISOABBREVIATION: Aust N Z J Psychiatry |
| YEAR: 2022 |
| MONTH: Apr |
| DAY: 11 |
| MEDLINEDATE: |
| SEASON: |
| CITEDMEDIUM: Internet |
| ISSN: 1440-1614 |
| ISSNTYPE: Electronic |
|
| MEDLINE JOURNAL |
|
| MEDLINETA: Aust N Z J Psychiatry |
| COUNTRY: England |
| ISSNLINKING: 0004-8674 |
| NLMUNIQUEID: 0111052 |
|
| PUBLICATION TYPE |
|
| PUBLICATIONTYPE TEXT |
| Journal Article |
|
| COMMENTS AND CORRECTIONS |
|
|
| GRANTS |
|
|
| GENERAL NOTE |
|
|
| KEYWORDS |
|
| KEYWORD |
| Suicide |
| causal inference |
| complex traits |
| genetics |
| risk factors |
|
| MESH HEADINGS |
|
|
| SUPPLEMENTARY MESH |
|
|
| GENE SYMBOLS |
|
|
| CHEMICALS |
|
|
| OTHER ID's |
|
|
|
