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Click here to search FindAPhD.com for PhD studentship opportunitiesAbout the Project
Mutimorbity (MM) is a major challenge facing health services and increases risk of disability, functional decline, polypharmacy, health care deficiencies, poor quality of life and reduced life expectancy. Working with the recently funded “LIfespaN multimorbidity research Collaborative: LINC” team (MR/W014416/1), this PhD will contribute to the characterisation and understanding of the development of Physical and Mental Health Multimorbidity (PMH MM) across the lifespan and to identify opportunities for prevention and intervention by discovering key causal contributions to MM.
In order to understand and prevent the development of multimorbid chronic disease, it is logical that a life course approach is needed. Starting from childhood, impacted by genetic, neurodevelopmental and environmental, risk factors accumulate over the time, ultimately culminating into MM. In order to “zoom in” on an aspect of this which is both measurable and manageable for the proposed PhD, work will focus on variable adiposity and the constellation of events which surround this risk factor as a key early part of possible later MM. Obesity and/or variable levels of adiposity often co-occur with other mental health (anxiety, depression, schizophrenia) and neurodevelopmental disorders. This cluster represents a clinically important co-occurrence of diseases and is a focus of the LINC project.
Aim and Objectives
Aim 1
Identify MM clusters: Identify the presence of MM clusters (with a focus on clusters of adiposity related phenotypes) within well powered adult cohort studies – in principle UKBB.
Aim 2
Explore genetic contributions to MM clusters: Analyse the association between genetic variation and MM clusters, and describe the genetic architecture and environmental precursors of MM.
Aim 3
Assess the association between MM cluster genotypes and life course data in available cohorts with differing time-point and demographic data frames. This stage will include further phenotype analysis in childhood to characterise and assess trajectories of cluster related phenotypes.
Methodology
Aim 1
Work within LINC will find adiposity driven MM clusters in later adulthood (UKBB:). This work will apply multivariate trajectory analysis of clinical cluster outcome in later adulthood. This work will also allow a comparison of clustering in later adulthood to that in earlier adulthood (via outcomes or intermediate measures). This will include data from earlier adulthood (ALSPAC and BiB parents, G&H) and potentially younger ages (ALSPAC, BiB, iPSYCH).
Aim 2
Genetic association studies of clusters identified in aim 1. This will principally involve analysis in UKBB for the presence of the genetic associations for these clusters – applying genomewide association study approaches .
Aim 3
Work will focus on characterising lifecourse footprints of the MM cluster genotypes identified in aims 1 and 2. This will be undertaken using both phenome wide association study approaches and methods able to account for multiple-testing in the context of correlated traits. This last stage will also look to compare the phenotypic footprint of cluster genotypes through time, using multiple methods for profile description to ask whether participants are closer to MM with age given genetic liability.
Keywords
Multimorbidity, BMI, adiposity, longitudinal, cohort, genetics, genetic epidemiology, epidemiology
How to apply for this project
This project will be based in Bristol Medical School - Population Health Sciences in the Faculty of Health Sciences at the University of Bristol.
Please visit the Faculty of Health Sciences website for details of how to apply
Funding Notes
The University of Bristol PGR scholarship pays tuition fees and a maintenance stipend (at the minimum UKRI rate) for the duration of a PhD (typically three years but can be up to four years).
References
2. Wade, K.H., Lam, B.Y.H., Melvin, A. et al. Loss-of-function mutations in the melanocortin 4 receptor in a UK birth cohort. Nat Med 27, 1088–1096 (2021).
3. Yengo L, Sidorenko J, Kemper KE, Zheng Z, Wood AR, Weedon MN, Frayling TM, Hirschhorn J, Yang J, Visscher PM; GIANT Consortium. Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry. Hum Mol Genet. 2018 Oct 15;27(20):3641-3649.
4. The relationship between severe mental illness and obesity. Postgrad Med;114(6 Suppl Managing Metabolic):28-39. doi: 10.3810/pgm.12.2003.suppl31.176. PMID: 19667651. 2003.

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