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Background: Coronary artery disease (CAD) is a complex, heterogeneous disease with distinct etiological mechanisms. These different etiologies may give rise to multiple subtypes of CAD that could benefit from alternative preventions and treatments. However, so far, there have been no systematic efforts to predict CAD subtypes using clinical and genetic factors., Methods: Here, we trained and applied statistical models incorporating clinical and genetic factors to predict CAD subtypes in 26 036 patients with CAD in the UK Biobank. We performed external validation of the UK Biobank models in the US-based All of Us cohort (8598 patients with CAD). Subtypes were defined as high versus normal LDL (low-density lipoprotein) levels, high versus normal Lpa (lipoprotein A) levels, ST-segment-elevation myocardial infarction versus non-ST-segment-elevation myocardial infarction, occlusive versus nonocclusive CAD, and stable versus unstable CAD. Clinical predictors included levels of ApoA, ApoB, HDL (high-density lipoprotein), triglycerides, and CRP (C-reactive protein). Genetic predictors were genome-wide and pathway-based polygenic risk scores (PRSs)., Results: Results showed that both clinical-only and genetic-only models can predict CAD subtypes, while combining clinical and genetic factors leads to greater predictive accuracy. Pathway-based PRSs had higher discriminatory power than genome-wide PRSs for the Lpa and LDL subtypes and provided insights into their etiologies. The 10-pathway PRS most predictive of the LDL subtype involved cholesterol metabolism. Pathway PRS models had poor generalizability to the All of Us cohort., Conclusions: In summary, we present the first systematic demonstration that CAD subtypes can be distinguished by clinical and genomic risk factors, which could have important implications for stratified cardiovascular medicine., Competing Interests: None.

While psychotic experiences are core symptoms of mental health disorders like schizophrenia, they are also reported by 5-10% of the population. Both smoking behaviour and genetic risk for psychiatric disorders have been associated with psychotic experiences, but the interplay between these factors remains poorly understood. We tested whether smoking status, maternal smoking around birth, and number of packs smoked/year were associated with lifetime occurrence of three psychotic experiences phenotypes: delusions (n = 2067), hallucinations (n = 6689), and any psychotic experience (delusions or hallucinations; n = 7803) in 157,366 UK Biobank participants. We next calculated polygenic risk scores for schizophrenia (PRS SCZ ), bipolar disorder (PRS BP ), major depression (PRS DEP ) and attention deficit hyperactivity disorder (PRS ADHD ) in 144,818 UK Biobank participants of European ancestry to assess whether association between smoking and psychotic experiences was attenuated after adjustment of diagnosis of psychiatric disorders and the PRSs. Finally, we investigated whether smoking exacerbates the effects of genetic predisposition on the psychotic phenotypes in gene-environment interaction models. Smoking status, maternal smoking, and number of packs smoked/year were associated with psychotic experiences (p < 1.77 × 10 -5 ). Except for packs smoked/year, effects were attenuated but remained significant after adjustment for diagnosis of psychiatric disorders and PRSs (p < 1.99 × 10 -3 ). Gene-environment interaction models showed the effects of PRS DEP and PRS ADHD (but not PRS SCZ or PRS BP ) on delusions (but not hallucinations) were significantly greater in current smokers compared to never smokers (p < 0.002). There were no significant gene-environment interactions for maternal smoking nor for number of packs smoked/year. Our results suggest that both genetic risk of psychiatric disorders and smoking status may have independent and synergistic effects on specific types of psychotic experiences.

There is extensive evidence of gender inequality in research leading to insufficient representation of women in leadership positions. Numbers revealing a gender gap in research are periodically reported by national and international institutions but data on perceptions of gender equality within the research community are scarce. In the present study, a questionnaire based on the British Athena Survey of Science, Engineering and Technology (ASSET 2016) was distributed among researchers working in Spain. Consistent with the original UK-based study, women in research perceived a greater degree of gender inequality than men. This difference was consistent from junior to senior positions, within public and private universities as well as research centres, and across all research disciplines. When responses were compared with the existing UK-based questionnaire, researchers in Spain felt that women and men are treated more equally in the workplace, yet they perceived their home departments to be less supportive regarding matters of gender equality. The results of this study provide clear evidence that men and women do not share the same perceptions of gender equality in science and that their differing perceptions are relatively consistent across two major European countries. The fact that men occupy the majority of senior positions while not perceiving the same inequality as women do, may be critical when it comes to ensuring the fair ascent of women to senior positions in an academic system. These data encourage the implementation of measures to ensure that both men and women are aware of gender biases in research., Competing Interests: The authors have declared that no competing interests exist.