A new transdisciplinary research model to investigate and improve the health of the public

Transdisciplinary research approaches are being applied to today's complex health problems, including the climate crisis and widening inequalities. Diverse forms of disciplinary and experiential knowledge are required to understand these challenges and develop workable solutions. We aimed to create an updated model reflective of the strengths and challenges of current transdisciplinary health research that can be a guide for future studies. We searched Medline using terms related to transdisciplinary, health and research. We coded data deductively and inductively using thematic analysis to develop a preliminary model of transdisciplinary research. The model was tested and improved through: (i) a workshop with 27 participants at an international conference in Xiamen, China and (ii) online questionnaire feedback from included study authors. Our revised model recommends the following approach: (i) co-learning, an ongoing phase that recognizes the distributed nature of knowledge generation and learning across partners; (ii) (pre-)development, activities that occur before and during project initiation to establish a shared mission and ways of working; (iii) reflection and refinement to evaluate and improve processes and results, responding to emergent information and priorities as an ongoing phase; (iv) conceptualization to develop goals and the study approach by combining diverse knowledge; (v) investigation to conduct the research; (vi) implementation to use new knowledge to solve societal problems. The model includes linear and cyclical processes that may cycle back to project development. Our new model will support transdisciplinary research teams and their partners by detailing the necessary ingredients to conduct such research and achieve health impact

Cost-effectiveness of population based BRCA testing with varying Ashkenazi Jewish ancestry

BACKGROUND: Population-based BRCA1/BRCA2 testing has been found to be cost-effective compared with family history-based testing in Ashkenazi-Jewish women were >30 years old with 4 Ashkenazi-Jewish grandparents. However, individuals may have 1, 2, or 3 Ashkenazi-Jewish grandparents, and cost-effectiveness data are lacking at these lower BRCA prevalence estimates. We present an updated cost-effectiveness analysis of population BRCA1/BRCA2 testing for women with 1, 2, and 3 Ashkenazi-Jewish grandparents. METHODS: Lifetime costs and effects of population and family history-based testing were compared with the use of a decision analysis model: 56% BRCA carriers are missed by family history criteria alone. Analyses were conducted for United Kingdom and United States populations. STUDY DESIGN: Model parameters were obtained from the Genetic Cancer Prediction through Population Screening trial and published literature. Model parameters and BRCA population prevalence for individuals with 3, 2, or 1 Ashkenazi-Jewish grandparent were adjusted for the relative frequency of BRCA mutations in the Ashkenazi-Jewish and general populations. Incremental cost-effectiveness ratios were calculated for all Ashkenazi-Jewish grandparent scenarios. Costs, along with outcomes, were discounted at 3.5%. The time horizon of the analysis is "life-time," and perspective is "payer." Probabilistic sensitivity analysis evaluated model uncertainty. RESULTS: Population testing for BRCA mutations is cost-saving in Ashkenazi-Jewish women with 2, 3, or 4 grandparents (22-33 days life-gained) in the United Kingdom and 1, 2, 3, or 4 grandparents (12-26 days life-gained) in the United States populations, respectively. It is also extremely cost-effective in women in the United Kingdom with just 1 Ashkenazi-Jewish grandparent with an incremental cost-effectiveness ratio of £863 per quality-adjusted life-years and 15 days life gained. Results show that population-testing remains cost-effective at the £20,000-30000 per quality-adjusted life-years and $100,000 per quality-adjusted life-years willingness-to-pay thresholds for all 4 Ashkenazi-Jewish grandparent scenarios, with ≥95% simulations found to be cost-effective on probabilistic sensitivity analysis. Population-testing remains cost-effective in the absence of reduction in breast cancer risk from oophorectomy and at lower risk-reducing mastectomy (13%) per risk-reducing salpingo-oophorectomy (20%) rates. CONCLUSION: Population testing for BRCA mutations with varying levels of Ashkenazi-Jewish ancestry is cost-effective in the United Kingdom and the United States. These results support population testing in Ashkenazi-Jewish women with 1-4 Ashkenazi-Jewish grandparent ancestry.Supported by “The Eve Appeal” charity, which had no role in the study design, data collection, analysis, interpretation, writing of the report, or decision to submit for publication. The research team was independent of funders. I.J. and U.M. have a financial interest in Abcodia, Ltd, which is a company formed to develop academic and commercial development of biomarkers for screening and risk prediction; I.J. is a member of the board of Abcodia Ltd and a Director of Women’s Health Specialists Ltd. R.M. declares funding for research from Cancer Research UK and Barts and the London Charity outside this submitted work and an honorarium for grant review from Israel National institute for Health Policy Research. The other authors declare no conflict of interest

Spatial variation and hot-spots of district level diarrhea incidences in Ghana: 2010–2014

Background: Diarrhea is a public health menace, especially in developing countries. Knowledge of the biological and anthropogenic characteristics is abundant. However, little is known about its spatial patterns especially in developing countries like Ghana. This study aims to map and explore the spatial variation and hot-spots of district level diarrhea incidences in Ghana. Methods: Data on district level incidences of diarrhea from 2010 to 2014 were compiled together with population data. We mapped the relative risks using empirical Bayesian smoothing. The spatial scan statistics was used to detect and map spatial and space-Time clusters. Logistic regression was used to explore the relationship between space-Time clustering and urbanization strata, i.e. rural, peri-urban, and urban districts. Results: We observed substantial variation in the spatial distribution of the relative risk. There was evidence of significant spatial clusters with most of the excess incidences being long-Term with only a few being emerging clusters. Space-Time clustering was found to be more likely to occur in peri-urban districts than in rural and urban districts. Conclusion: This study has revealed that the excess incidences of diarrhea is spatially clustered with peri-urban districts showing the greatest risk of space-Time clustering. More attention should therefore be paid to diarrhea in peri-urban districts. These findings also prompt public health officials to integrate disease mapping and cluster analyses in developing location specific interventions for reducing diarrhea

UK consensus recommendations for clinical management of cancer risk for women with germline pathogenic variants in cancer predisposition genes: RAD51C, RAD51D, BRIP1 and PALB2.

Germline pathogenic variants (GPVs) in the cancer predisposition genes BRCA1, BRCA2, MLH1, MSH2, MSH6, BRIP1, PALB2, RAD51D and RAD51C are identified in approximately 15% of patients with ovarian cancer (OC). While there are clear guidelines around clinical management of cancer risk in patients with GPV in BRCA1, BRCA2, MLH1, MSH2 and MSH6, there are few guidelines on how to manage the more moderate OC risk in patients with GPV in BRIP1, PALB2, RAD51D and RAD51C, with clinical questions about appropriateness and timing of risk-reducing gynaecological surgery. Furthermore, while recognition of RAD51C and RAD51D as OC predisposition genes has been established for several years, an association with breast cancer (BC) has only more recently been described and clinical management of this risk has been unclear. With expansion of genetic testing of these genes to all patients with non-mucinous OC, new data on BC risk and improved estimates of OC risk, the UK Cancer Genetics Group and CanGene-CanVar project convened a 2-day meeting to reach a national consensus on clinical management of BRIP1, PALB2, RAD51D and RAD51C carriers in clinical practice. In this paper, we present a summary of the processes used to reach and agree on a consensus, as well as the key recommendations from the meeting

PGRMC1 phosphorylation affects cell shape, motility, glycolysis, mitochondrial form and function, and tumor growth.

BackgroundProgesterone Receptor Membrane Component 1 (PGRMC1) is expressed in many cancer cells, where it is associated with detrimental patient outcomes. It contains phosphorylated tyrosines which evolutionarily preceded deuterostome gastrulation and tissue differentiation mechanisms.ResultsWe demonstrate that manipulating PGRMC1 phosphorylation status in MIA PaCa-2 (MP) cells imposes broad pleiotropic effects. Relative to parental cells over-expressing hemagglutinin-tagged wild-type (WT) PGRMC1-HA, cells expressing a PGRMC1-HA-S57A/S181A double mutant (DM) exhibited reduced levels of proteins involved in energy metabolism and mitochondrial function, and altered glucose metabolism suggesting modulation of the Warburg effect. This was associated with increased PI3K/AKT activity, altered cell shape, actin cytoskeleton, motility, and mitochondrial properties. An S57A/Y180F/S181A triple mutant (TM) indicated the involvement of Y180 in PI3K/AKT activation. Mutation of Y180F strongly attenuated subcutaneous xenograft tumor growth in NOD-SCID gamma mice. Elsewhere we demonstrate altered metabolism, mutation incidence, and epigenetic status in these cells.ConclusionsAltogether, these results indicate that mutational manipulation of PGRMC1 phosphorylation status exerts broad pleiotropic effects relevant to cancer and other cell biology

Genetic Variants at Chromosomes 2q35, 5p12, 6q25.1, 10q26.13, and 16q12.1 Influence the Risk of Breast Cancer in Men

Male breast cancer accounts for approximately 1% of all breast cancer. To date, risk factors for male breast cancer are poorly defined, but certain risk factors and genetic features appear common to both male and female breast cancer. Genome-wide association studies (GWAS) have recently identified common single nucleotide polymorphisms (SNPs) that influence female breast cancer risk; 12 of these have been independently replicated. To examine if these variants contribute to male breast cancer risk, we genotyped 433 male breast cancer cases and 1,569 controls. Five SNPs showed a statistically significant association with male breast cancer: rs13387042 (2q35) (odds ratio (OR)  = 1.30, p = 7.98×10−4), rs10941679 (5p12) (OR = 1.26, p = 0.007), rs9383938 (6q25.1) (OR = 1.39, p = 0.004), rs2981579 (FGFR2) (OR = 1.18, p = 0.03), and rs3803662 (TOX3) (OR = 1.48, p = 4.04×10−6). Comparing the ORs for male breast cancer with the published ORs for female breast cancer, three SNPs—rs13387042 (2q35), rs3803662 (TOX3), and rs6504950 (COX11)—showed significant differences in ORs (p<0.05) between sexes. Breast cancer is a heterogeneous disease; the relative risks associated with loci identified to date show subtype and, based on these data, gender specificity. Additional studies of well-defined patient subgroups could provide further insight into the biological basis of breast cancer development

Recommendations for laboratory workflow that better support centralised amalgamation of genomic variant data: findings from CanVIG-UK national molecular laboratory survey.

BACKGROUND: National and international amalgamation of genomic data offers opportunity for research and audit, including analyses enabling improved classification of variants of uncertain significance. Review of individual-level data from National Health Service (NHS) testing of cancer susceptibility genes (2002-2023) submitted to the National Disease Registration Service revealed heterogeneity across participating laboratories regarding (1) the structure, quality and completeness of submitted data, and (2) the ease with which that data could be assembled locally for submission. METHODS: In May 2023, we undertook a closed online survey of 51 clinical scientists who provided consensus responses representing all 17 of 17 NHS molecular genetic laboratories in England and Wales which undertake NHS diagnostic analyses of cancer susceptibility genes. The survey included 18 questions relating to 'next-generation sequencing workflow' (11), 'variant classification' (3) and 'phenotypical context' (4). RESULTS: Widely differing processes were reported for transfer of variant data into their local LIMS (Laboratory Information Management System), for the formatting in which the variants are stored in the LIMS and which classes of variants are retained in the local LIMS. Differing local provisions and workflow for variant classifications were also reported, including the resources provided and the mechanisms by which classifications are stored. CONCLUSION: The survey responses illustrate heterogeneous laboratory workflow for preparation of genomic variant data from local LIMS for centralised submission. Workflow is often labour-intensive and inefficient, involving multiple manual steps which introduce opportunities for error. These survey findings and adoption of the concomitant recommendations may support improvement in laboratory dataflows, better facilitating submission of data for central amalgamation

Calculating Stage Duration Statistics in Multistage Diseases

Many human diseases are characterized by multiple stages of progression. While the typical sequence of disease progression can be identified, there may be large individual variations among patients. Identifying mean stage durations and their variations is critical for statistical hypothesis testing needed to determine if treatment is having a significant effect on the progression, or if a new therapy is showing a delay of progression through a multistage disease. In this paper we focus on two methods for extracting stage duration statistics from longitudinal datasets: an extension of the linear regression technique, and a counting algorithm. Both are non-iterative, non-parametric and computationally cheap methods, which makes them invaluable tools for studying the epidemiology of diseases, with a goal of identifying different patterns of progression by using bioinformatics methodologies. Here we show that the regression method performs well for calculating the mean stage durations under a wide variety of assumptions, however, its generalization to variance calculations fails under realistic assumptions about the data collection procedure. On the other hand, the counting method yields reliable estimations for both means and variances of stage durations. Applications to Alzheimer disease progression are discussed

Measurement of the branching fraction and CP content for the decay B(0) -> D(*+)D(*-)

This is the pre-print version of the Article. The official published version can be accessed from the links below. Copyright @ 2002 APS.We report a measurement of the branching fraction of the decay B0→D*+D*- and of the CP-odd component of its final state using the BABAR detector. With data corresponding to an integrated luminosity of 20.4  fb-1 collected at the Υ(4S) resonance during 1999–2000, we have reconstructed 38 candidate signal events in the mode B0→D*+D*- with an estimated background of 6.2±0.5 events. From these events, we determine the branching fraction to be B(B0→D*+D*-)=[8.3±1.6(stat)±1.2(syst)]×10-4. The measured CP-odd fraction of the final state is 0.22±0.18(stat)±0.03(syst).This work is supported by DOE and NSF (USA), NSERC (Canada), IHEP (China), CEA and CNRS-IN2P3 (France), BMBF (Germany), INFN (Italy), NFR (Norway), MIST (Russia), and PPARC (United Kingdom). Individuals have received support from the A.P. Sloan Foundation, Research Corporation, and Alexander von Humboldt Foundation