Predicting loneliness with polygenic scores of social, psychological and psychiatric traits

Abdellaoui, Abdel; Nivard, Michel G.; Hottenga, Jouke‐Jan; Fedko, Iryna O.; Verweij, Karin J. H.; Baselmans, Bart M. L.; Ehli, Erik A.; Davies, Gareth E.; Bartels, Meike; Boomsma, Dorret I.; Cacioppo, John T.

doi:10.1111/gbb.12472

Cited by 38 publications

(29 citation statements)

References 96 publications

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“…Contrary to the phenotypic associations, few studies have investigated the genetic associations between well-being and well-being related traits. A genetic investigation of loneliness (Abdellaoui et al 2018 ) revealed a strong negative association between a polygenic score for loneliness and subjective well-being, and a positive association with neuroticism and depression, indicating genetic links between the 3-WBS and loneliness. With regard to self-rated health, twin studies have demonstrated that both genes and the environment contribute to the association with well-being (Roysamb et al 2003 ), but to our knowledge no molecular genetic study has been conducted yet.…”

Section: Introductionmentioning

confidence: 99%

A Genetic Investigation of the Well-Being Spectrum

et al. 2019

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The interrelations among well-being, neuroticism, and depression can be captured in a so-called well-being spectrum (3-phenotype well-being spectrum, 3-WBS). Several other human traits are likely linked to the 3-WBS. In the present study, we investigate how the 3-WBS can be expanded. First, we constructed polygenic risk scores for the 3-WBS and used this score to predict a series of traits that have been associated with well-being in the literature. We included information on loneliness, big five personality traits, self-rated health, and flourishing. The 3-WBS polygenic score predicted all the original 3-WBS traits and additionally loneliness, self-rated health, and extraversion (R 2 between 0.62% and 1.58%). Next, using LD score regression, we calculated genetic correlations between the 3-WBS and the traits of interest. From all candidate traits, loneliness and self-rated health were found to have the strongest genetic correlations ( r g = − 0.79, and r g = 0.64, respectively) with the 3-WBS. Lastly, we use Genomic SEM to investigate the factor structure of the proposed spectrum. The best model fit was obtained for a two-factor model including the 5-WBS traits, with two highly correlated factors representing the negative- and positive end of the spectrum. Based on these analyses we propose to include loneliness and self-rated health in the WBS and use a 5-phenotype well-being spectrum in future studies to gain more insight into the determinants of human well-being. Electronic supplementary material The online version of this article (10.1007/s10519-019-09951-0) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

A Genetic Investigation of the Well-Being Spectrum

et al. 2019

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“…Over 34 out of the 60 traits in the genetic correlation analyses showed a significant genetic association with loneliness, suggesting widespread shared genetic influences (e.g., pleiotropic effects) or causal relationships between loneliness and several traits. MDD has been strongly associated with loneliness in previous studies [52][53][54] , but evidence from longitudinal studies indicates that loneliness and depression are conceptually and statistically different constructs. [53][54][55] Our results confirm the strong biological ties between loneliness, major depression, and depressive symptoms in both research ascertained samples and EHR from a hospital population.…”

Section: Discussionmentioning

confidence: 89%

Phenome-wide Investigation of Health Outcomes Associated with Genetic Predisposition to Loneliness

Abdellaoui

Sanchez‐Roige

Sealock

et al. 2018

Preprint

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Humans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. While the experience of loneliness is universally human, some people report experiencing greater loneliness than others.Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. While it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition towards loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we conducted a genome-wide association (GWAS) meta-analysis of loneliness (N=475,661), report 12 associated loci (two novel) and significant genetic correlations with 34 other complex traits. The polygenic basis for loneliness was significantly enriched for evolutionary constrained genes and genes expressed in specific brain tissues: (frontal) cortex, cerebellum, anterior cingulate cortex, and substantia nigra. We built polygenic scores based on this GWAS meta-analysis to explore the genetic association between loneliness and health outcomes in an independent sample of 18,498 individuals for whom electronic health records were available. A genetic predisposition towards loneliness predicted cardiovascular, psychiatric, and metabolic disorders, and triglycerides and highdensity lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, effect of body fat on loneliness, and a similar weaker causal effect of BMI. Our results provide a framework for ongoing studies of the genetic basis of loneliness and its role in mental and physical health.

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“…These findings complement several lines of evidence. First, previous studies report the strongest correlations between loneliness and neuroticism or extraversion (Atak, 2009; Teppers et al, 2013; Mund and Neyer, 2016), although several studies also identify correlations of loneliness with openness, agreeableness and conscientiousness (Lopes et al, 2003; Abdellaoui et al, 2018b). Second, loneliness and neuroticism exhibited a considerable genetic overlap measured by both genetic variants and familial relationships (Abdellaoui et al, 2018a).…”

Section: Discussionmentioning

confidence: 99%

Connectome-based individualized prediction of loneliness

Feng

Wang

et al. 2019

Social Cognitive and Affective Neuroscience

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Loneliness is an increasingly prevalent condition linking with enhanced morbidity and premature mortality. Despite recent proposal on medicalization of loneliness, so far no effort has been made to establish a model capable of predicting loneliness at the individual level. Here, we applied a machine-learning approach to decode loneliness from whole-brain resting-state functional connectivity (RSFC). The relationship between whole-brain RSFC and loneliness was examined in a linear predictive model. The results revealed that individual loneliness could be predicted by within- and between-network connectivity of prefrontal, limbic and temporal systems, which are involved in cognitive control, emotional processing and social perceptions and communications, respectively. Key nodes that contributed to the prediction model comprised regions previously implicated in loneliness, including the dorsolateral prefrontal cortex, lateral orbital frontal cortex, ventromedial prefrontal cortex, caudate, amygdala and temporal regions. Our findings also demonstrated that both loneliness and associated neural substrates are modulated by levels of neuroticism and extraversion. The current data-driven approach provides the first evidence on the predictive brain features of loneliness based on organizations of intrinsic brain networks. Our work represents initial efforts in the direction of making individualized prediction of loneliness that could be useful for diagnosis, prognosis and treatment.

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Predicting loneliness with polygenic scores of social, psychological and psychiatric traits

Cited by 38 publications

References 96 publications

A Genetic Investigation of the Well-Being Spectrum

A Genetic Investigation of the Well-Being Spectrum

Phenome-wide Investigation of Health Outcomes Associated with Genetic Predisposition to Loneliness

Connectome-based individualized prediction of loneliness

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