Purpose Cancer and cardiovascular disease (CVD) are common causes of morbidity and mortality, and measurement and interpretation of their co-occurrence rate have important implications for public health and patient care. Here, we present the raw and adjusted co-occurrence rates of cancer and CVD in the overall population by using a visually intuitive network approach.
Methods By using baseline survey and linked health outcome data from 490,842 individuals age 40 to 69 years from the UK Biobank, we recorded diagnoses between 1997 and 2014 of specific cancers and specific CVDs ascertained through hospital claims. We measured raw and adjusted rates of CVD for the following groups: individuals with Hodgkin or non-Hodgkin lymphoma, lung and trachea cancer, uterus cancer, colorectal cancer, prostate cancer, breast cancer, or no recorded diagnosed cancer during this time period. Analysis accounted for age, sex, and behavioral risk factors, without regard to the order of occurrence of cancer and CVD.
Results A significantly increased rate of CVD was found in patients with multiple types of cancers, including Hodgkin and non-Hodgkin lymphoma and lung and trachea, uterus, colorectal, and breast cancer, compared with patients without cancer by using age and sex-adjusted models. Increased co-occurrence for many CVD categories remained after correction for behavioral risk factors. Construction of co-occurrence networks highlighted heart failure as a shared CVD diagnosis across multiple cancer types, including breast cancer, lung cancer, non-Hodgkin lymphoma, and colorectal cancer. Smoking, physical activity, and other lifestyle factors accounted for some but not all of the increased co-occurrence for many of the CVD diagnoses.
Conclusion Increased co-occurrence of several common CVD conditions is seen widely across multiple malignancies, and shared diagnoses, such as heart failure, were highlighted by using network methods.
Publication: Visualization of Cancer and Cardiovascular Disease Co-Occurrence With Network Methods Christine W. Duarte, Volkhard Lindner, Sanjeev A. Francis, and Dounya Schoormans JCO Clinical Cancer Informatics 2017 :1, 1-12
Elevated plasma levels of Cthrc1 in subjects with red hair: What are the consequences for bone, liver, vascular disease, diabetes and muscle?
We discovered that Cthrc1 is novel hormone made by the pituitary gland (Stohn et al. PlosOne 2012). Studies in mice showed that absence of Cthrc1 causes fatty liver formation, reduced grip strength and reduced bone density. Having established a sensitive assay, we found that Cthrc1 plasma levels in healthy subjects are very low with the exception of subjects with red hair (melanocortin receptor-1 variants) who had up to several hundred fold higher levels. Therefore, we are very interested how hair color and melanocortin receptor-1 genotype (when available) correlates with grip strength, bone density, vascular disease, diabetes and steatosis. The frequency of mutant melanocortin receptor-1 alleles in northern european countries such as the UK are estimated to be 50%. It is established that subjects with red hair and associated non-tanning skin are more likely to develop skin cancer, yet the mutant allele does not appear to be under selective pressure in these countries. If we find positive correlations between red hair (and assumed elevated Cthrc1 blood levels) and increased bone density, grip strength and resistance to fatty liver formation, future therapies can be developed to treat osteoporosis, muscle weakness and liver disease. The database will be mined for correlations between red hair, non- or poorly tanning skin versus darker, easily tanning skin with respect to osteoporosis, bone mineral density (heel BMD), bone fractures, hand grip strength, atherosclerosis, vascular disease, alcoholic liver disease and fatty liver. In addition, we would be very interested in obtaining information on the melanocortin receptor-1 genotype when it becomes available (July 2015?). The latter will predict to what degree signaling via the melanocortin receptor-1 is inhibited. We would like to include the full cohort for analysis.
|Lead investigator:||Dr Volkhard Lindner|
|Lead institution:||Maine Medical Center Research Institute|
|794||Visualization of cancer and cardiovascular disease co-occurrence with network methods||Duarte et al||2017||JCO Clinical Cancer Informatics 2017|