B3830 - Metabolic subtypes and longitudinal trajectories from childhood to adults - 02/08/2021

B number: 
B3830
Principal applicant name: 
Ville-Petteri Makinen | South Australian Health and Medical Research Institute (Australia)
Co-applicants: 
Professor Mika Ala-Korpela
Title of project: 
Metabolic subtypes and longitudinal trajectories from childhood to adults
Proposal summary: 

Understanding how metabolic problems develop is of fundamental interest to the people with age-associated diseases and their families and there is strong community interest in protecting young people from a life-long trajectory towards a diabetic or otherwise metabolically unfavourable future. In recent years, childhood obesity has emerged as an important phenomenon that is projected to increase the number of people with high cardiometabolic risk when the young generations grow old. In the first phase, we will describe how a population of children at risk will eventually develop cardiometabolic risk factors later in their life using unprecedented longitudinal datasets and sophisticated statistical techniques. If additional funding is achieved for the second stage, we will also investigate if the combination of genetics and childhood trajectories of development would allow us to identify the most susceptible individuals and thus ultimately provide the parents with the information that they can use to take preventative action. The lead investigator has developed a statistical framework that allows us to integrate multiple time points and multiple biomarkers simultaneously across partially incomplete datasets. Such a multi-decadal and multi-variable view of metabolic dysfunction is scientifically unique and we also expect to derive novel information about the diversity of metabolic trajectories within real-world human populations. This epidemiological information will be useful for public health policy makers who wish to mitigate the adverse health impacts due to the prevailing obesity-promoting environment. Our study will provide a detailed biochemical fingerprint of the trajectory that carries the highest risk for late-life diseases that can guide nutritional inputs and other life style factors within preventative strategies.

Impact of research: 
The proposed use of the ALSPAC data is an important step towards our ultimate goal of characterizing the development of human metabolism from cradle to grave. The world population is at an inflection point towards an inverted age pyramid where the old outnumber the young. Simultaneously, the world is struggling with the obesity pandemic that is jeopardizing the health of future generations. While animal studies have established the basic biology of aging during an organism's life span, substantial quantitative follow-up data from humans is surprisingly sparse and much of the ageing research is still based on cross-sectional comparisons of old and young individuals. A fully integrated and statistically robust model of the human life span and the diversity of those life spans within real-world populations will produce explicit evidence on who and how is at the greatest risk of specific diseases and overall burden of late-onset morbidity. We maintain that such information will be essential if we are to meet the challenges of ageing populations in the coming decades.
Date proposal received: 
Wednesday, 21 July, 2021
Date proposal approved: 
Monday, 2 August, 2021
Keywords: 
Epidemiology, Cancer, Diabetes, Hypertension, Obesity, Computer simulations/modelling/algorithms, Metabolomics, Statistical methods, Ageing, Biomarkers - e.g. cotinine, fatty acids, haemoglobin, etc., Metabolic - metabolism, Physical - activity, fitness, function, Sex differences, Statistical methods, Blood pressure, BMI, Cardiovascular, Growth, Hormones - cortisol, IGF, thyroid, Immunity, Kidney function, Liver function