TY - JOUR
T1 - Loneliness and depression
T2 - bidirectional mendelian randomization analyses using data from three large genome-wide association studies
AU - Sbarra, David A.
AU - Ramadan, Ferris A.
AU - Choi, Karmel W.
AU - Treur, Jorien L.
AU - Levey, Daniel F.
AU - Wootton, Robyn E.
AU - Stein, Murray B.
AU - Gelernter, Joel
AU - Klimentidis, Yann C.
N1 - Funding Information: DAS was partialy supported by a grant from the National Institute of Aging (R01AG078361-01). KWC was partially supported by a Kaplen Fellowship on Depression from the Harvard Medical School, a NARSAD Young Investigator Grant from the Brain & Behavior Research Foundation, and funding from the National Institute of Mental Health (K08MH127413). DFL was supported by a NARSAD Young Investigator Grant from the Brain & Behavior Research Foundation. REW is supported by a postdoctoral fellowship from the South-Eastern Regional Health Authority (2020024). Funding Information: MBS in the past 3 years has received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, Bionomics, BioXcel Therapeutics, Clexio, EmpowerPharm, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech. He has also received research support from NIH, Department of Veterans Affairs, and the Department of Defense. He is on the scientific advisory board for Brain and Behavior Research Foundation and the Anxiety and Depression Association of America. Dr. Stein has stock options in Oxeia Biopharmaceuticals and Epivario. Publisher Copyright: © 2023, The Author(s), under exclusive licence to Springer Nature Limited.
PY - 2023
Y1 - 2023
N2 - Major depression (MD) is a serious psychiatric illness afflicting nearly 5% of the world’s population. A large correlational literature suggests that loneliness is a prospective risk factor for MD; correlational assocations of this nature may be confounded for a variety of reasons. This report uses Mendelian Randomization (MR) to examine potentially causal associations between loneliness and MD. We report on analyses using summary statistics from three large genome wide association studies (GWAS). MR analyses were conducted using three independent sources of GWAS summary statistics. In the first set of analyses, we used available summary statistics from an extant GWAS of loneliness to predict MD risk. We used two sources of outcome data: the Psychiatric Genomics Consortium (PGC) meta-analysis of MD (PGC-MD; N = 142,646) and the Million Veteran Program (MVP-MD; N = 250,215). Finally, we reversed analyses using data from the MVP and PGC samples to identify risk variants for MD and used loneliness outcome data from UK Biobank. We find robust evidence for a bidirectional causal relationship between loneliness and MD, including between loneliness, depression cases status, and a continuous measure of depressive symptoms. The estimates remained significant across several sensitivity analyses, including models that account for horizontal pleiotropy. This paper provides the first genetically-informed evidence that reducing loneliness may play a causal role in decreasing risk for depressive illness, and these findings support efforts to reduce loneliness in order to prevent or ameliorate MD. Discussion focuses on the public health significance of these findings, especially in light of the SARS-CoV-2 pandemic.
AB - Major depression (MD) is a serious psychiatric illness afflicting nearly 5% of the world’s population. A large correlational literature suggests that loneliness is a prospective risk factor for MD; correlational assocations of this nature may be confounded for a variety of reasons. This report uses Mendelian Randomization (MR) to examine potentially causal associations between loneliness and MD. We report on analyses using summary statistics from three large genome wide association studies (GWAS). MR analyses were conducted using three independent sources of GWAS summary statistics. In the first set of analyses, we used available summary statistics from an extant GWAS of loneliness to predict MD risk. We used two sources of outcome data: the Psychiatric Genomics Consortium (PGC) meta-analysis of MD (PGC-MD; N = 142,646) and the Million Veteran Program (MVP-MD; N = 250,215). Finally, we reversed analyses using data from the MVP and PGC samples to identify risk variants for MD and used loneliness outcome data from UK Biobank. We find robust evidence for a bidirectional causal relationship between loneliness and MD, including between loneliness, depression cases status, and a continuous measure of depressive symptoms. The estimates remained significant across several sensitivity analyses, including models that account for horizontal pleiotropy. This paper provides the first genetically-informed evidence that reducing loneliness may play a causal role in decreasing risk for depressive illness, and these findings support efforts to reduce loneliness in order to prevent or ameliorate MD. Discussion focuses on the public health significance of these findings, especially in light of the SARS-CoV-2 pandemic.
UR - http://www.scopus.com/inward/record.url?scp=85171685898&partnerID=8YFLogxK
U2 - https://doi.org/10.1038/s41380-023-02259-w
DO - https://doi.org/10.1038/s41380-023-02259-w
M3 - Article
C2 - 37735503
SN - 1359-4184
JO - Molecular psychiatry
JF - Molecular psychiatry
ER -