Age at first birth in women is genetically associated with increased risk of schizophrenia

Prof. Paunio on PGC:n jäsenPrevious studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.Peer reviewe

Topological Data Analysis Reveals Antimicrobial Resistotypes Associated to the Microbiome in Bronchiectasis:An International Multi-centre Study

Introduction: While prior work has reported on microorganisms and resistance independently, no study to date has integrated these data for clinical value in bronchiectasis. Methods: Shotgun metagenomics to evaluate microbiome and resistance profiles was performed on the Cohort of Asian and Matched European Bronchiectasis 2 (CAMEB2) (n=251) recruited from four countries(Singapore, Malaysia, Italy, and the United Kingdom) and ‘matched’ by age, sex, exacerbation frequency and lung function. Spectral clustering was implemented to assess for resistotypes (RTs)and topological data analysis (TDA) with PCoA (as lens) applied to integrate microbiomes, RTs, and clinical outcomes. Results: Unsupervised analysis reveals two RTs: RT1, characterized bymacrolide and tetracycline resistance and RT2, abundant for multidrug efflux genes. Integrative analysis by TDA reveals several associations between specific bacteria, RTs, and clinical outcomes including (1) Haemophilus influenzae, RT1, moderate disease severity and non-exacerbator status and (2) Pseudomonas aeruginosa,RT2, and post-TB bronchiectasis aetiology.Conclusion: Spectral clustering and integrative analysis using a TDA framework identifies non-linear complex associations between the microbiome, resistance profile and clinical outcomes within bronchiectasis with significant potential for improved patient risk stratification using next-generation sequencing. Funding: Singapore Ministry of Health's National Medical Research Council under its Clinician Scientist Award (MOH-000710) (S.H.C)