Every fourth woman suffers from uterine leiomyomas (ULs) – benign tumors of the uterine smooth muscle wall - at some point in premenopausal life. ULs, also called myomas or fibroids, cause a substantial health burden through symptoms such as excessive uterine bleeding, abdominal pain and infertility. These tumors are the most common cause of hysterectomy. Considering the impact that ULs have to women’s health, they are severely understudied. Our breakthrough work has shed important new light on the biology and genesis of ULs. In this ERC proposal we hypothesize that ULs can emerge through several distinct mechanisms and anticipate that each mechanism contributes to somewhat different tumor biology, clinicopathological features, and response to treatment. Also, we hypothesize that predisposing genetic variants may confer susceptibility to a particular UL subclass. To test these hypotheses, we shall create multiple layers of high-throughput data on clinicopathologically characterized ULs, including copy number variation, whole genome sequence, gene expression, and methylome profiles. Integration of these data should establish the existence and key characteristics of the different UL subclasses. Finally, we shall examine the effect of currently used drugs as well as new lead compounds in response to treatment, stratified per UL subclass. These efforts will 1) provide biological insight into molecular mechanisms driving the UL genesis and lay the scientific basis of their molecular classification, 2) describe the key characteristics of each class, 3) provide key biomarkers and molecular tools for routine diagnosis of UL subclasses, as well as clues to their targeted treatment, and 4) produce tools for detection of hereditary predisposition to ULs. This ERC project will be an important step towards non-invasive management of ULs. Reaching this goal would benefit hundreds of millions of women.

NPF-PANDA aims for a multi-method assessment of cluster dynamics in urban environments during new particle formation. New particle formation by gas-to-particle conversion is frequently detected in the atmosphere, but, according to the current understanding, should not proceed in heavily polluted urban areas, where large amounts of primary aerosol particles are present acting as sink for both condensable vapours and newly formed clusters. However, it is nonetheless observed in Chinese megacities where it even can promote haze formation and hence impact urban air quality. It is under debate, whether this is linked to faster cluster growth or a less effective condensation sink than commonly assumed. NPF-PANDA will quantify urban cluster size-distributions below 3 nm with a multi-instrument approach and novel data analysis methods. This will lead to unprecedented high quality data of the cluster dynamics and solve the role of fast growth on the survival probability of newly formed clusters under high condensation sink. By combining measurements from urban Beijing with precisely tailored laboratory experiments at the CERN CLOUD chamber, the magnitude of the underlying microphysical growth processes like coagulation or condensation will be disentangled and the effects of different precursor gases can be tested. Cluster dynamics simulations will back-up the experimental findings and via a detailed comparison of measured and simulated size-distributions, this will reveal information on cluster stability and the cluster-stabilizing role of different bases. Altogether, the project will be an essential part in solving the “China-NPF-puzzle” and hence impact future air quality research and air pollution mitigation, which is also highly relevant for medium-polluted European cities.

The COVID-19 pandemic placed a heavy social and health burden on populations. Yet, because of social inequalities in the pandemic’s impact on fertility behaviour, babies conceived during the pandemic may be the most socially advantaged and healthiest birth cohort of the last decades. Research on this counterintuitive but realistic consequence of the pandemic – the Lockdown Cohort (LoCo)-Effect – is critical for public policy and the understanding of pandemic consequences. As individual-level register data for babies conceived and born in 2021 and later is only just becoming available, we still know little about how the pandemic changed the composition of parents and to what extent this explains changes in birth outcomes for those born during the pandemic. To address this knowledge gap, I will use individual-level register data (2010-2022) from Finland, Scotland, Austria, Spain, the United States, and Brazil and natural experimental methods to study the LoCo-effect comparatively. This strengthens the generalisability of results across different welfare regimes and pandemic experiences. First, I will study the magnitude of compositional changes in parental characteristics due to the unequal impact of the pandemic on fertility. Second, I will analyse the extent to which differences in prematurity and birth weight between the LoCo and earlier cohorts are caused by this change in parental characteristics. Third, I will estimate how the pandemic has affected intersectional social inequalities in birthweight and preterm birth. This project is innovative because it bridges disconnected debates in demography, epidemiology, and sociology to explain why, against expectations, pregnancy and birth outcomes have improved during the pandemic. As parental characteristics and birth outcomes shape health, developmental, and socioeconomic outcomes throughout life, the results of this project will influence social and public health research and policy for decades to come.