Abstract
Influence of loneliness on human survival has been established epidemiologically, but genomic research remains undeveloped. We identified 34 loneliness-associated genes which were statistically significant for high- lonely and low-lonely individuals. With the univariate Cox proportional hazards regression model, we obtained corresponding regression coefficients for loneliness-associated genes fo individual cancer patients. Furthermore, risk scores could be generated with the combination of gene expression level multiplied by corresponding regression coefficients of loneliness-associated genes. We verified that high-risk score cancer patients had shorter mean survival time than their low-risk score counterparts. Then we validated the loneliness-associated gene signature in three independent brain cancer cohorts with Kaplan-Meier survival curves (n=77, 85 and 191), significantly separable by log-rank test with hazard ratios (HR) >1 and p-values <0.0001 (HR=2.94, 3.82, and 1.78). Moreover, we validated the loneliness-associated gene signature in bone cancer (HR=5.10, p-value=4.69e-3), lung cancer (HR=2.86, p-value=4.71e-5), ovarian cancer (HR=1.97, p-value=3.11e-5), and leukemia (HR=2.06, p-value=1.79e-4) cohorts. The last lymphoma cohort proved to have an HR=3.50, p-value=1.15e-7. Loneliness- associated genes had good survival prediction for cancer patients, especially bone cancer patients. Our study provided the first indication that expression of loneliness-associated genes are related to survival time of cancer patients.
Highlights
The influence of loneliness on human health has been verified by epidemiologically, histologically, and genomically
Our study provided the first indication that expression of loneliness-associated genes are related to survival time of cancer patients
Our study focused on loneliness-associated genes for survival prediction in different kinds of cancer patients, and the results showed that loneliness-associated genes influenced the survival time of cancer patients
Summary
The influence of loneliness (social isolation) on human health has been verified by epidemiologically, histologically, and genomically. With gene expression of a genome, survival prediction in cancer patients was improved over histologic grades. Two articles derived the survival significant genes and implemented Cox proportional hazards model to predict survival between high-risk and low-risk patients in non-small cell lung cancer (Hsu et al, 2009; Hou et al, 2010). We concluded that the difference of loneliness-associated genes are statistically significant in high-lonely and lowlonely individuals, and with Cox proportional hazards regression model, we got the risk scores of each patients with the combination of gene expression level multiplied the corresponding regression coefficients of the lonelinessassociated genes.
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