Health status and quality of life among older adults in rural Tanzania

BACKGROUND\ud \ud Increasingly, human populations throughout the world are living longer and this trend is developing in sub-Saharan Africa. In developing African countries such as Tanzania, this demographic phenomenon is taking place against a background of poverty and poor health conditions. There has been limited research on how this process of ageing impacts upon the health of older people within such low-income settings.\ud \ud OBJECTIVE\ud \ud The objective of this study is to describe the impacts of ageing on the health status, quality of life and well-being of older people in a rural population of Tanzania.\ud \ud DESIGN\ud \ud A short version of the WHO Survey on Adult Health and Global Ageing questionnaire was used to collect information on the health status, quality of life and well-being of older adults living in Ifakara Health and Demographic Surveillance System, Tanzania, during early 2007. Questionnaires were administered through this framework to 8,206 people aged 50 and over.\ud \ud RESULTS\ud \ud Among people aged 50 and over, having good quality of life and health status was significantly associated with being male, married and not being among the oldest old. Functional ability assessment was associated with age, with people reporting more difficulty in performing routine activities as age increased, particularly among women. Reports of good quality of life and well-being decreased with increasing age. Women were significantly more likely to report poor quality of life (odds ratio 1.31; p<0.001, 95% CI 1.15-1.50).\ud \ud CONCLUSIONS\ud \ud Older people within this rural Tanzanian setting reported that the ageing process had significant impacts on their health status, quality of life and physical ability. Poor quality of life and well-being, and poor health status in older people were significantly associated with marital status, sex, age and level of education. The process of ageing in this setting is challenging and raises public health concerns

Ovarian cancer

Ovarian cancer is not a single disease and can be subdivided into at least five different histological subtypes that have different identifiable risk factors, cells of origin, molecular compositions, clinical features and treatments. Ovarian cancer is a global problem, is typically diagnosed at a late stage and has no effective screening strategy. Standard treatments for newly diagnosed cancer consist of cytoreductive surgery and platinum-based chemotherapy. In recurrent cancer, chemotherapy, anti-angiogenic agents and poly(ADP-ribose) polymerase inhibitors are used, and immunological therapies are currently being tested. High-grade serous carcinoma (HGSC) is the most commonly diagnosed form of ovarian cancer and at diagnosis is typically very responsive to platinum-based chemotherapy. However, in addition to the other histologies, HGSCs frequently relapse and become increasingly resistant to chemotherapy. Consequently, understanding the mechanisms underlying platinum resistance and finding ways to overcome them are active areas of study in ovarian cancer. Substantial progress has been made in identifying genes that are associated with a high risk of ovarian cancer (such as BRCA1 and BRCA2), as well as a precursor lesion of HGSC called serous tubal intraepithelial carcinoma, which holds promise for identifying individuals at high risk of developing the disease and for developing prevention strategies

Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease

We sought to identify new susceptibility loci for Alzheimer's disease through a staged association study (GERAD+) and by testing suggestive loci reported by the Alzheimer's Disease Genetic Consortium (ADGC) in a companion paper. We undertook a combined analysis of four genome-wide association datasets (stage 1) and identified ten newly associated variants with P ≤ 1 × 10−5. We tested these variants for association in an independent sample (stage 2). Three SNPs at two loci replicated and showed evidence for association in a further sample (stage 3). Meta-analyses of all data provided compelling evidence that ABCA7 (rs3764650, meta P = 4.5 × 10−17; including ADGC data, meta P = 5.0 × 10−21) and the MS4A gene cluster (rs610932, meta P = 1.8 × 10−14; including ADGC data, meta P = 1.2 × 10−16) are new Alzheimer's disease susceptibility loci. We also found independent evidence for association for three loci reported by the ADGC, which, when combined, showed genome-wide significance: CD2AP (GERAD+, P = 8.0 × 10−4; including ADGC data, meta P = 8.6 × 10−9), CD33 (GERAD+, P = 2.2 × 10−4; including ADGC data, meta P = 1.6 × 10−9) and EPHA1 (GERAD+, P = 3.4 × 10−4; including ADGC data, meta P = 6.0 × 10−10)

Steroid receptor coactivator-1 modulates the function of Pomc neurons and energy homeostasis

Hypothalamic neurons expressing the anorectic peptide Pro-opiomelanocortin (Pomc) regulate food intake and body weight. Here, we show that Steroid Receptor Coactivator-1 (SRC-1) interacts with a target of leptin receptor activation, phosphorylated STAT3, to potentiate Pomc transcription. Deletion of SRC-1 in Pomc neurons in mice attenuates their depolarization by leptin, decreases Pomc expression and increases food intake leading to high-fat diet-induced obesity. In humans, fifteen rare heterozygous variants in SRC-1 found in severely obese individuals impair leptin-mediated Pomc reporter activity in cells, whilst four variants found in non-obese controls do not. In a knock-in mouse model of a loss of function human variant (SRC-1L1376P), leptin-induced depolarization of Pomc neurons and Pomc expression are significantly reduced, and food intake and body weight are increased. In summary, we demonstrate that SRC-1 modulates the function of hypothalamic Pomc neurons, and suggest that targeting SRC-1 may represent a useful therapeutic strategy for weight loss.Peer reviewe

Low-frequency variation in TP53 has large effects on head circumference and intracranial volume.

Cranial growth and development is a complex process which affects the closely related traits of head circumference (HC) and intracranial volume (ICV). The underlying genetic influences shaping these traits during the transition from childhood to adulthood are little understood, but might include both age-specific genetic factors and low-frequency genetic variation. Here, we model the developmental genetic architecture of HC, showing this is genetically stable and correlated with genetic determinants of ICV. Investigating up to 46,000 children and adults of European descent, we identify association with final HC and/or final ICV + HC at 9 novel common and low-frequency loci, illustrating that genetic variation from a wide allele frequency spectrum contributes to cranial growth. The largest effects are reported for low-frequency variants within TP53, with 0.5 cm wider heads in increaser-allele carriers versus non-carriers during mid-childhood, suggesting a previously unrecognized role of TP53 transcripts in human cranial development

The UK10K project identifies rare variants in health and disease

M. Kivimäki työryhmäjäsen.The contribution of rare and low-frequency variants to human traits is largely unexplored. Here we describe insights from sequencing whole genomes (low read depth, 7x) or exomes (high read depth, 80x) of nearly 10,000 individuals from population-based and disease collections. In extensively phenotyped cohorts we characterize over 24 million novel sequence variants, generate a highly accurate imputation reference panel and identify novel alleles associated with levels of triglycerides (APOB), adiponectin (ADIPOQ) and low-density lipoprotein cholesterol (LDLR and RGAG1) from single-marker and rare variant aggregation tests. We describe population structure and functional annotation of rare and low-frequency variants, use the data to estimate the benefits of sequencing for association studies, and summarize lessons from disease-specific collections. Finally, we make available an extensive resource, including individual-level genetic and phenotypic data and web-based tools to facilitate the exploration of association results.Peer reviewe