I. Millwood

Adiposity and risk of breast cancer in 280 000 Chinese women: a prospective cohort study

Abstract Background Adiposity is associated with increased risk of breast cancer in post-menopausal women, while the association appears to be the inverse among premenopausal women in Western populations, but is unclear for Chinese women. Methods Using data on 284 538 women with no history of cancer, hysterectomy, oophorectomy, or breast surgery at baseline in 2004–8 from the China Kadoorie Biobank (a prospective cohort study), Cox regression was used to estimate adjusted hazard ratios (HRs) for breast cancer and its subtypes by measured body mass index (BMI) and other adiposity measures (waist circumference, fat percentage, waist–hip ratio, fat mass) and by self-reported BMI at age 25 years. Results Mean BMI was 23.8 (3.5 SD) kg/m2 at baseline (mean age 51.4 years) and 21.9 (2.7 SD) kg/m2 at age 25 years. During 10 years of follow-up, there were 2379 incident breast cancer cases. Higher BMI was associated with a higher risk of breast cancer in women who were post-menopausal [HR = 1.35, 95% confidence interval (CI) 1.24–1.47] and premenopausal (HR = 1.13, 95% CI 1.03–1.24) at baseline, but not when censoring at age 50 years to capture mainly premenopausal cancers. Among post-menopausal women, BMI was associated with oestrogen-receptor positive (ER ) (HR = 1.47, 95% CI 1.24–1.74), but not with oestrogen-receptor negative (ER−) breast cancer (HR = 1.02, 95% CI 0.75–1.37). Waist circumference and fat percentage were associated with a higher risk of breast cancer. Conclusion In this cohort of Chinese women, higher levels of general and central adiposity were associated with a higher risk of breast cancer, in both women who were premenopausal and women who were post-menopausal at baseline. Among post-menopausal women, adiposity was associated with ER   but not ER − breast cancer.

Proteomics in cardiology: research and practice.

Despite recent advances in prevention and treatment, cardiovascular disease (CVD) remains a leading cause of premature death and disability globally, with a rising burden in many low- and middle-income countries. Several modifiable determinants of CVD are well-established (eg, smoking, hypertension, obesity, dyslipidaemia), but they do not fully explain temporal trends and large variations in disease rates between different populations. Moreover, the causal relevance of certain CVD risk factors and/or their associated biological mechanisms is still incompletely understood. High-throughput affinity-based proteomic assays now enable quantification of several thousand protein markers in the blood, and their application in large epidemiological and clinical studies will facilitate the development of precision cardiovascular medicine. This review describes recent findings from large population-based studies to illustrate the value of proteomics in cardiology for improved risk prediction, diagnosis and patient stratification; better understanding of disease aetiology and pathophysiology; and identification of repurposing and novel therapeutic targets. To overcome the current limitations, future studies should aim to further increase the sample size, number of proteins measured reliably (eg, via multiple assay platforms) and longitudinally, and ancestry population diversity, to expedite clinical translation of key research findings that will help to transform development of precision medicine in cardiology globally.

A scalable high-throughput serolomics platform for profiling serum antibody responses in large-scale population-based cohorts.