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Background: Amino acid metabolism is dysregulated in colorectal cancer patients; however, it is not clear whether pre-diagnostic levels of amino acids are associated with subsequent risk of colorectal cancer. We investigated circulating levels of amino acids in relation to colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank cohorts. Methods: Concentrations of 13-21 amino acids were determined in baseline fasting plasma or serum samples in 654 incident colorectal cancer cases and 654 matched controls in EPIC. Amino acids associated with colorectal cancer risk following adjustment for the false discovery rate (FDR) were then tested for associations in the UK Biobank, for which measurements of 9 amino acids were available in 111,323 participants, of which 1221 were incident colorectal cancer cases. Results: Histidine levels were inversely associated with colorectal cancer risk in EPIC (odds ratio [OR] 0.80 per standard deviation [SD], 95% confidence interval [CI] 0.69–0.92, FDR P-value=0.03) and in UK Biobank (HR 0.93 per SD, 95% CI 0.87–0.99, P-value=0.03). Glutamine levels were borderline inversely associated with colorectal cancer risk in EPIC (OR 0.85 per SD, 95% CI 0.75–0.97, FDR P-value=0.08) and similarly in UK Biobank (HR 0.95, 95% CI 0.89–1.01, P=0.09) In both cohorts, associations changed only minimally when cases diagnosed within 2 or 5 years of follow-up were excluded. Conclusions: Higher circulating levels of histidine were associated with a lower risk of colorectal cancer in two large prospective cohorts. Further research to ascertain the role of histidine metabolism and potentially that of glutamine in colorectal cancer development is warranted. [ABSTRACT FROM AUTHOR]

Simple Summary: (Multi-)Morbidity shares common biological mechanisms or risk factors with breast cancer. However, the risk of breast cancer among women with (multi-)morbidity remains unclear. In this study, using data of 239,436 female participants aged 40–69 of the UK Biobank cohort, we identified five chronic disease patterns: no-predominant morbidity, psychiatric morbidities, respiratory/immunological morbidities, cardiovascular/metabolic morbidities, and unspecific morbidities. After a median follow-up of 7 years, 5326 women developed breast cancer. We found no association between breast cancer risk and either the number of chronic diseases or chronic disease patterns, apart from an increased risk among women aged younger than 50 with a psychiatric pattern. Women with any multi-morbidity were more likely to die or to be diagnosed with other cancers. Our findings suggest that multi-morbidity may not be a key factor to help identify patients at an increased risk of breast cancer. (Multi-)Morbidity shares common biological mechanisms or risk factors with breast cancer. This study aimed to investigate the association between the number of morbidities and patterns of morbidity and the risk of female breast cancer. Among 239,436 women (40–69 years) enrolled in the UK Biobank cohort who had no cancer history at baseline, we identified 35 self-reported chronic diseases at baseline. We assigned individuals into morbidity patterns using agglomerative hierarchical clustering analysis. We fitted Cox models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for breast cancer risk. In total, 58.4% of women had at least one morbidity, and the prevalence of multi-morbidity was 25.8%. During a median 7-year follow-up, there was no association between breast cancer risk (5326 cases) and either the number of morbidities or the identified clinically relevant morbidity patterns: no-predominant morbidity (reference), psychiatric morbidities (HR = 1.04, 95%CI 0.94–1.16), respiratory/immunological morbidities (HR = 0.98, 95%CI 0.90–1.07), cardiovascular/metabolic morbidities (HR = 0.93, 95%CI 0.81–1.06), and unspecific morbidities (HR = 0.98, 95%CI 0.89–1.07), overall. Among women younger than 50 years of age only, however, there was a significant association with psychiatric morbidity patterns compared to the no-predominant morbidity pattern (HR = 1.25, 95%CI 1.02–1.52). The other associations did not vary when stratifying by age at baseline and adherence to mammography recommendations. In conclusion, multi-morbidity was not a key factor to help identify patients at an increased risk of breast cancer. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the association between thyroid dysfunction and breast cancer risk. We included 239,436 females of the UK Biobank cohort. Information on thyroid dysfunction, personal and family medical history, medications, reproductive factors, lifestyle, and socioeconomic characteristics was retrieved from baseline self‐reported data and hospital inpatient databases. Breast cancer diagnoses were identified through population‐based registries. We computed Cox models to estimate hazard ratios (HRs) of breast cancer incidence for thyroid dysfunction diagnosis and treatments, and examined potential confounding and effect modification by comorbidities and breast cancer risk factors. In our study, 3,227 (1.3%) and 20,762 (8.7%) women had hyper‐ and hypothyroidism prior to the baseline. During a median follow‐up of 7.1 years, 5,326 (2.2%) women developed breast cancer. Compared to no thyroid dysfunction, there was no association between hypothyroidism and breast cancer risk overall (HR = 0.93, 95% confidence interval (CI): 0.84–1.02, 442 cases), but we found a decreased risk more than 10 years after hypothyroidism diagnosis (HR=0.85, 95%CI 0.74–0.97, 226 cases). There was no association with hyperthyroidism overall (HR=1.08, 95%CI 0.86–1.35, 79 cases) but breast cancer risk was elevated among women with treated hyperthyroidism (HR=1.38, 95%CI: 1.03–1.86, 44 cases) or aged 60 years or more at hyperthyroidism diagnosis (HR=1.74, 95%CI: 1.01–3.00, 113 cases), and 5–10 years after hyperthyroidism diagnosis (HR=1.58, 95%CI: 1.06–2.33, 25 cases). In conclusion, breast cancer risk was reduced long after hypothyroidism diagnosis, but increased among women with treated hyperthyroidism. Future studies are needed to determine whether the higher breast cancer risk observed among treated hyperthyroidism could be explained by hyperthyroidism severity, type of treatment or aetiology. [ABSTRACT FROM AUTHOR]

Different lifestyle patterns across Europe may influence plasma concentrations of B-vitamins and one-carbon metabolites and their relation to chronic disease. Comparison of published data on one-carbon metabolites in Western European regions is difficult due to differences in sampling procedures and analytical methods between studies. The present study aimed, to compare plasma concentrations of one-carbon metabolites in Western European regions with one laboratory performing all biochemical analyses. We performed the present study in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort among 5446 presumptively healthy individuals. Quantile regression was used to compare sex-specific median concentrations between Northern (Denmark and Sweden), Central (France, Germany, The Netherlands and United Kingdom) and Southern (Greece, Spain and Italy) European regions. The lowest folate concentrations were observed in Northern Europe (men, 10·4 nmol/l; women, 10·7 nmol/l) and highest concentrations in Central Europe. Cobalamin concentrations were slightly higher in Northern Europe (men, 330 pmol/l; women, 352 pmol/l) compared with Central and Southern Europe, but did not show a clear north–south gradient. Vitamin B2 concentrations were highest in Northern Europe (men, 22·2 nmol/l; women, 26·0 nmol/l) and decreased towards Southern Europe (Ptrend< 0·001). Vitamin B6 concentrations were highest in Central Europe in men (77·3 nmol/l) and highest in the North among women (70·4 nmol/l), with decreasing concentrations towards Southern Europe in women (Ptrend< 0·001). In men, concentrations of serine, glycine and sarcosine increased from the north to south. In women, sarcosine increased from Northern to Southern Europe. These findings may provide relevant information for the study of regional differences of chronic disease incidence in association with lifestyle. [ABSTRACT FROM PUBLISHER]