35th Annual Meeting of the European Association for the Study of Diabetes

Genetic risk for schizophrenia and autism, social impairment and developmental pathways to psychosis

“…Eligible were singletons born to a known mother and resident in Denmark on their 1st birthday. Cases in iPSYCH2012 54 were defined from the Danish Psychiatric Central Research Register 55 with diagnosis date no later than 2012, and the controls constitute a random sample from the set of eligible children. Cases in the iPSYCH ASD sample are defined as subjects in iPSYCH2012 53 having an ASD diagnosis (ICD codes F84.0, F84.1, F84.5, F84.8, or F84.9) given no later than 2013, and controls did not have an ASD diagnosis by 2013.…”

Identifying Phenogroups in Patients with Subclinical Diastolic Dysfunction Using Unsupervised Statistical Learning

“…In this retrospective study of 162 patients with asymptomatic diastolic dysfunction who were matched by known outcome (remaining asymptomatic vs. developing HFpEF), we used unsupervised machine learning to determine whether patients could be clustered into groups of similar phenotypes which would be predictive of developing HFpEF. In this process, we found (14) patients with asymptomatic diastolic dysfunction were a heterogeneous group with different risk profiles (2) all clusters contained some patients who would progress to develop HFpEF (3) the identified phenogroups had differential outcomes, indicating different risk profiles and clinical trajectories (4) certain co-morbidities were risk factors for developing HFpEF across the entire cohort and other risk factors for developing HFpEF were restricted to specific clusters/phenogroups and (5) the time interval between developing HFpEF and death was similar regardless of cluster assignment (data not shown).to This study showed that it was feasible to subdivide asymptomatic diastolic dysfunction patients, who have not yet progressed to clinical HFpEF, early in the disease process into smaller more homogeneous phenogroups with welldefined risk factors for progression to HFpEF and different clinical trajectories. This approach may be useful to identify those patients with subclinical diastolic dysfunction who are at higher risk and who may benefit from tailored preventive strategies.…”

“…The cohort contained 67.9% female, and 77.8% white patients. Patients who progressed to HFpEF were more likely to have a history of diabetes mellitus (DM), chronic kidney disease (18), and atrial fibrillation (14), as well as the use of digoxin and diuretics. In contrast, the use of aldosterone antagonists was more prevalent in the patient cohort who remained in asymptomatic diastolic dysfunction.…”

“…Analysis of variance (ANOVA) Ao (Aortic) Atrial fibrillation (14) Chronic kidney disease (18) Diabetes mellitus (DM) End-diastolic volume index (24) End-systolic volume index (19) Ejection fraction (EF)…”

“…The remaining patients were further sub-divided into two groups: (14) those who had clinical heart failure during the study period, and (2) those who remained in asymptomatic diastolic dysfunction.…”