The purpose of the Centre for Population Health Research (POPC) is to advance multidisciplinary health research focusing on different phases of the life cycle and to develop new modelling methods with the help of which national registers and clinical population research data could be utilised for predicting and promoting population health, well-being, and functional ability.
Data and sample collections in many of the POPC cohorts have continued for several decades. Amongst them are landmark studies that represent some of the best-characterised life-course data sets worldwide with repeated and detailed measurements and bio-specimen collections (e.g. serum, stool, semen, hair, breast milk). The data in these cohorts form a multidisciplinary platform for diverse health research that can be considered unique with global standards. These datasets and bio-specimen collections with links to national health registries, social living environments, geographical information systems, biodiversity characteristics of built and natural environment offer exceptional opportunities to examine the determinants of health and the causes of non-communicable diseases with a very broad spectrum. As the cohort participants age and continue to be followed with regular examinations, the possibilities to examine the aetiologies of a variety of human health outcomes becomes increasingly better in the future. The ongoing research projects address key health topics, such as cardiovascular disorders, diabetes, healthy ageing, neurodegenerative diseases, depression, reproductive health, and the health consequences of psychosocial stress. A unique characteristic of these studies is their capability to form multigenerational cohorts that will provide novel insights to the mechanisms and aetiology of health outcomes via intergenerational transmission. In POPC, we have active cross-cohort collaboration and we support combination of the cohort data. All work is supported by interdisciplinary research teams.
Cohorts currently affiliated with the POPC:
Key words:
microbiome/metagenome bioinformatics, computational microbiome research, statistical and machine learning techniques in human (gut) microbiome research, statistical ecology and epidemiology of human gut microbiome, multi-omic data integration in microbiome population cohort studies, cardiovascular disease/health, cognition, physical activity, sleep, diet, healthy aging, brain imaging, brain health, epigenetics, population-based cohort studies, intergenerational, health development, stress
Key research themes and areas of expertise – all related to multigenerational & reproductive health:
Gut microbiota and health across life-span
Computational microbiome research: we are looking for a postdoctoral researcher to work on computational modeling, integration and analysis of human gut microbiome population cohorts. These recently (metagenome-)profiled cohorts comprise several representative studies from Finland, with altogether >10,000 fecal samples across the life span and three generations of families, complemented by comprehensive population register data and host phenotyping. This allows understanding the links between microbiome variation, host health, demographics, and life style. The setup provides opportunities to adapt existing statistical, machine learning, and bioinformatics techniques to data-intensive problems in ecological and epidemiological modeling of the human microbiome, as well as to design and implement new (open source) analysis strategies in this research area. The work is supported by close collaboration and networking opportunities with local and international experts in computational microbiome research. Gut microbiota and health: we are also looking for a postdoctoral researcher to work on various health aspects related to gut microbiota. Several health/disease phenotypes are available in the POPC cohorts. We value expertise in a range of fields, e.g. in medicine, microbiology, nutrition, public health and epidemiology.
Key words:
metagenome, microbiome, statistical ecology, data science, epidemiology, population cohorts
Cardiometabolic health and its determinants across life-span
We seek for a postdoctoral researcher/researchers to work on diverse topics related to cardiometabolic health and diseases and their determinants across the lifespan. The available cohort studies are initially targeted on specific life-stages, such as childhood and adolescence, mid-life, time of retirement, and old age, but due to extensive follow-up periods these cohorts provide excellent opportunity to examine health development from childhood to midlife or from mid-life to old age, for example. The cohort studies housed at the POPC have multifaceted longitudinal data on cardiometabolic health and diseases, including markers of vascular health assessed with ultrasound as well as serum metabolomics and lipidomics. In addition, the extensive data banks further entail repeated data on behavior-related cardiovascular risk factors, such as accelerometer-measured physical activity, sedentary behavior, and sleep, as well as diet, and psychosocial stress. We value expertise in a range of fields, e.g. in medicine, public health, epidemiology and statistics.
Cognition and brain health across life-span
We seek for postdoctoral researchers with interest to focus on diverse topics linked to neurocognitive function, brain health and neurodegeneration as well as on their determinants across the life-course. Cohort studies have collected longitudinal data e.g. on cognitive function from participants covering the lifespan from early childhood to old-age, and also multigenerational cognitive function data is available. The collection of these data has been harmonized in part of the cohorts by using similar measurement methods between the cohorts, which enables easy cross-cohort collaboration. In addition to cognitive function data, some of the cohorts have collected data on brain structures and function using e.g. structural and functional MRI techniques, and other domains of neuropsychological functioning and socio-emotional development. The detailed brain imaging data covers specifically the early years of the life-course, but imaging data is available also from adulthood. In relation to neurodegenerative aspects, the existing extensive sample biobank has been leveraged to measure neurodegenerative biomarkers from human plasma using ultrasensitive methods. Together with the clinical follow-up data from childhood to adulthood, the biomarker data allows focusing e.g. on early determinants of neurodegenerative processes. We value expertise e.g. in medicine, neuroscience, psychology, public health, epidemiology, statistics.
Intergenerational epigenetics
We are looking a post-doctoral researcher to work in projects that aim at breakthroughs in our understanding of non-genetic inheritance of human phenotypes via germline epigenome. The mechanisms of non-genetic inheritance have started to be revealed in experimental animals. Due to challenges in setting up multigenerational studies, however, the evidence has remained weak in humans. To advance science in this field, we have initiated the collection of multigenerational data in our cohorts, including sperm samples for epigenetic analyses. These data enable the testing of the hypothesis in humans that parental exposure to a stressor such as diet, smoking, environmental toxicants or psychosocial stress causes health effects in the offspring via epigenetic changes in the gametes. In combination with animal experiments that dissect the mechanistic details of the process, these projects will have potential to reveal the importance of non-genetic inheritance in human health. Importantly, the germline-related studies will be supported by our active research on male reproductive health and spermatogenesis in both human and mice. A demonstration of an inheritance with such functional mechanism in humans – which essentially implies the inheritance of acquired characteristics – would lead to fundamental conceptual change in scientific thinking and have potentially huge ramifications for public health.