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OBJECTIVE: This study aimed to assess the heterogeneity and stability of cognition in patients with a non-affective psychotic disorder and their unaffected siblings. In addition, we aimed to predict the cognitive subtypes of siblings by their probands. METHOD: Assessments were conducted at baseline, 3 and 6 years in 1119 patients, 1059 siblings and 586 controls from the Genetic Risk and Outcome of Psychosis (GROUP) study. Group-based trajectory modeling was applied to identify trajectories and clustered multinomial logistic regression analysis was used for prediction modeling. A composite score of eight neurocognitive tests was used to measure cognitive performance. RESULTS: Five stable cognitive trajectories ranging from severely altered to high cognitive performance were identified in patients. Likewise, four stable trajectories ranging from moderately altered to high performance were found in siblings. Siblings had a higher risk of cognitive alteration when patients' alteration was mild (OR = 2.21), moderate (OR = 5.70), and severe (OR = 10.07) compared with patients with intact cognitive function. The familial correlation coefficient between pairs of index patients and their siblings was 0.27 (P = 0.003). CONCLUSIONS: The cognitive profiles identified in the current study might be suitable as endophenotypes and could be used in future genetic studies and predicting functional and clinical outcomes. ispartof: Acta Psychiatrica Scandinavica vol:138 issue:6 pages:591-604 ispartof: location:United States status: published

Background: The number of older people living with cancer and cardiometabolic conditions is increasing, but little is known about how specific combinations of these conditions impact mortality. Methods: A total of 22,692 participants aged 65 years and older from four international cohorts were followed-up for mortality for an average of 10 years (8,596 deaths). Data were harmonized across cohorts and mutually exclusive groups of disease combinations were created for cancer, myocardial infarction (MI), stroke, and diabetes at baseline. Cox proportional hazards models for all-cause mortality were used to estimate the age- and sex-adjusted hazard ratio and rate advancement period (RAP) (in years). Results: At baseline, 23.6% (n = 5,116) of participants reported having one condition and 4.2% (n = 955) had two or more conditions. Data from all studies combined showed that the RAP increased with each additional condition. Diabetes advanced the rate of dying by the most years (5.26 years; 95% confidence interval [CI], 4.53-6.00), but the effect of any single condition was smaller than the effect of disease combinations. Some combinations had a significantly greater impact on the period by which the rate of death was advanced than others with the same number of conditions, for example, 10.9 years (95% CI, 9.4-12.6) for MI and diabetes versus 6.4 years (95% CI, 4.3-8.5) for cancer and diabetes. Conclusions: Combinations of cancer and cardiometabolic conditions accelerate mortality rates in older adults differently. Although most studies investigating mortality associated with multimorbidity used disease counts, these provide little guidance for managing complex patients as they age. © The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved.