Genetic discovery for loneliness

To identify genetic variation predisposing to loneliness, we performed a GWAS in the UK Biobank study (max sample N = 452,302) on the self-reported responses to three related questions ascertaining to perceived loneliness, frequency of social interactions, and ability to confide in someone. Results from these three GWAS were then combined using multi-trait GWAS (MTAG)8 into a single discovery sample, yielding an effective sample size of 487,647 individuals (see Methods). Across these data we estimated the heritability of loneliness to be 4.2% (S.E 0.02) and identified 15 genomic loci at genome-wide significance (P < 5 × 10−8, Fig. 1 Supplementary Data 1). A genetic risk score comprised of the 15 lead SNPs predicted loneliness in an independent set of 7556 individuals (P = 0.025).

Fig. 1 Manhattan plots for the four social interaction traits. In each case the green horizontal dotted line denotes genome-wide significance, and the highlighted SNPs are in loci within 300 kb of the identified signals. In the case of loneliness (top panel) the results are from multi-trait GWAS, in the other cases the results are from linear mixed models Full size image

By integrating gene expression and epigenetic data we sought to identify the relevant cell/tissue types implicated in the regulation of loneliness. We observed enrichment of association signals in regions surrounding genes that are preferentially expressed in several brain tissues (e.g., cerebellum, basal ganglia, and cortex; Fig. 2 Supplementary Table 1), in addition to enrichment for several epigenetic marks also in the basal ganglia, cortex and foetal brain (Supplementary Data 2). We next used FUSION9 to identify individual genes implicated by associated eQTL effects in GTEx brain tissues (Supplementary Data 3). Across 9178 transcripts in 9 tissue types, we identified 8 gene transcripts with expression levels putatively linked-to susceptibility to loneliness (GPX1, C1QTNF4, C17orf58, MTCH2, BPTF, RP11-159N11.4, CRHR1-IT1 and PLEKHM1). BPTF encodes a transcription regulator that is highly expressed in foetal brain and is implicated in neurodegenerative diseases. GPX1 and MTCH2 are implicated in multiple metabolic pathways, including mitochondrial function.

Fig. 2 Genetic correlations and tissue enrichment results. Left: Genome-wide genetic correlations between regular participation in three different social activities–religious group (yellow), sports club /gym (blue), pub/social club (red). Right: Gene expression enrichment across genome-wide association results for the four social isolation and interaction traits, the green dotted line indicates Bonferroni corrected statistical significance Full size image

Estimating genetic overlap with other complex traits

Thirty-six complex traits exhibited significant genetic correlation with loneliness (Supplementary Data 4), including strong positive genetic overlap with neuroticism (r g = 0.69, P = 2 × 10−167), and depressive symptoms (r g = 0.84, P = 5.4 × 10−153), and strong negative genetic overlap with subjective well-being (r g = −0.72, P = 1.2 × 10−66) and years of education (r g = −0.33, P = 2.2 × 10−43). Given the high genetic correlation with depressive symptoms, we performed a sensitivity analysis by repeating the GWAS for loneliness excluding individuals with self-reported depression (N = 26,801). There was no appreciable change in test statistic across any of the 15 loci (Supplementary Data 1), median Chi-square value reduction ~13%), indicating that these loci do not influence loneliness via susceptibility to depression.

In addition to psychiatric and psychological traits, several anthropometric outcomes showed positive genetic correlations with loneliness (e.g., adult body mass index, BMI: r g = 0.17, P = 4.4 × 10−10). We assessed the likely causal direction between BMI and loneliness by testing a bi-directional Mendelian randomisation (MR) framework, using genetic instruments and/or datasets derived independently from UK Biobank where necessary (Table 1). We found evidence supporting a positive causal effect of BMI on loneliness (P IVW = 2.3 × 10−6), but not for loneliness on BMI (P IVW = 0.58). We repeated these analyses using depressive symptoms, instead of loneliness, and found evidence supporting a positive bi-directional causal relationship with BMI (BMI-to-depressive symptoms: P IVW = 0.017, depressive symptoms-to-BMI P WM = 9.2 × 10−4). These MR analyses suggest direct causal links between social well-being and cardio-metabolic health, but do not preclude the possibility that both traits are causally downstream of shared biological pathways10. The observed heterogeneity in these models also suggests that the links between these traits are complex.

Table 1 Mendelian randomisation results Full size table

Genetic discovery for engagement in social activities

To further explore potential biological mechanisms that confer susceptibility to social interactions, we performed additional GWAS analyses in the UK Biobank study for three further traits: regular attendance at a sports club or gym, pub or social club, and religious group (Fig. 1). The phenotypic overlaps between these traits are summarised in Supplementary Tables 2 and 3. Heritability estimates for these three traits ranged from 3.4% (sports club or gym) to 4.6% (religious group), placing them in the bottom 5% of heritability estimates for other complex traits, similar to other behavioural traits. We identified 38 genome-wide significant loci across the 3 traits (Fig. 1, Supplementary Data 5), of which 14 are correlated with previously reported signals for other behavioural/psychiatric traits (Supplementary Data 6). These traits demonstrated a partly shared genetic architecture–possibly indicating a shared propensity to social interactions (Supplementary Table 4).

We also observed trait-specific patterns of genetic correlations with other outcomes, concordant with reported non-genetic epidemiological correlations (Supplementary Data 4, Fig. 2). This trait specificity was supported by several of the individual loci (Supplementary Data 5); the most strongly associated variant for pub/social club attendance is a missense allele in the gene encoding alcohol dehydrogenase (ADH1B-rs1229984, P pub = 4.2 × 10−25), which showed little or no association with sports club (P = 1.1 × 10−2) or religious group (P = 9.0 × 10−1) attendance. Furthermore, a recently reported signal for risk-taking propensity11 showed far stronger association with sports/gym attendance (CADM2-rs7627971, P = 5.8 × 10−10) than pub/social club (P = 3.0 × 10−3) or religious group (P = 3.9 × 10−2) attendance.

In contrast, several loci demonstrated pleiotropy across a range of complex traits, notably at the 1p22.2-BARHL2 and 3p21.31-CAMKV regions. We identified two independent signals (r2 = 0.005, ~230Kb apart) near BARHL2, the first associated exclusively with pub/social club attendance (rs12759477, P pub = 2.4 × 10−13, P sport = 0.18, P religious = 0.14), and the second with all three social interaction traits (rs699534, P pub = 0.01, P sport = 1.5 × 10−6, P religious = 2.1 × 10−10). The latter signal is not correlated with a known signal for any other complex trait, whereas the former is partially correlated with reported signals for educational attainment (r2 = 0.08), chronotype (r2 = 0.27) and age at first sexual intercourse (r2 = 0.27). Similarly, at the 3p21.31-CAMKV region we identified two independent signals ~200 kb apart (r2 = 0.16). One signal, rs9837520, is associated primarily with religious group attendance (P religious = 2.6 × 10−8, P pub = 0.38, P sport = 0.03) and is correlated with reported signals for inflammatory bowel disease (r2 = 1) and educational attainment (r2 = 0.75). The other signal, rs11712056, is associated with all three social interaction traits (all P < 6.1 × 10−5), and is correlated with reported signals for educational attainment (r2 = 1), resting heart rate (r2 = 0.12), HDL cholesterol (r2 = 0.43), blood pressure (r2 = 0.27), childhood ear infections (r2 = 0.18), age at menarche (r2 = 0.11) and age at first sex/birth (r2 = 0.35).

Finally, we explored which cell and tissue types were most relevant to the underlying biological processes regulating these social traits by performing partitioned LD score regression (see Methods). Genetic associations for all four traits were enriched for localisation to genes expressed in the central nervous system (P min = 6 × 10−5, Fig. 2). When considering the 53 individual tissue types available in GTEx (Supplementary Data 2), significant (corrected P-value threshold 2.4 × 10−4) enrichments were seen for pub/social club attendance with the amygdala (brain) (P = 1.7 × 10−4) and for religious group attendance with the frontal cortex (P = 6.2 × 10−6), and in particular the anterior cingulate cortex (P = 1.1 × 10−4), which is located in the medial frontal lobe and is widely reported to regulate emotional self-control and problem-solving.

A limitation of our analysis was the absence of comparably sized independent replication studies to replicate associations with individual loci. This represents a challenge for genetic studies of complex traits with extremely large discovery datasets, such as UK Biobank, particularly for traits that are uncommonly measured. However, cumulative assessment of the polygenic risk score for loneliness in an unrelated sample that demonstrates the overall validity of our study design and analytical approach.

In summary, our findings highlight the specific genetic basis for social isolation and social interaction. We find evidence for shared genetic effects across social traits, in addition to more specific pathways that drive engagement in particular activities. Our findings also suggest a causal relationship between cardio-metabolic health and social isolation/mental health, an observation which warrants further investigation using other experimental approaches. Future studies should also aim to identify the potential mediators and modifiers that link mental health traits to obesity risk, such as eating behaviour, diet and physical activity. Finally, our findings provide a genetic resource for future studies to explore potential modifiable risk factors for social isolation.