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BACKGROUND: Characterizing neurocognitive endophenotypes of mental illnesses (MIs) could be useful for identifying at-risk individuals, increasing early diagnosis, improving disease subtyping, and proposing therapeutic strategies to reduce the negative effects of the symptoms, in addition to serving as a scientific basis to unravel the physiopathology of the disease. However, a standardized algorithm to determine cognitive endophenotypes has not yet been developed. The main objective of this study was to present a method for the identification of endophenotypes in MI research. METHODS: For this purpose, a 14-expert working group used a scoping review methodology and designed a method that includes a scoring template with five criteria and indicators, a strategy for their verification, and a decision tree. CONCLUSIONS: This work is ongoing since it is necessary to obtain external validation of the applicability of the method in future research.

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RESUMEN

BACKGROUND: Frailty is a common syndrome among older adults and patients with several comorbidities. Grip strength (GS) is a representative parameter of frailty because it is a valid indicator of current and long-term physical conditions in the general population and patients with severe mental illnesses (SMIs). Physical and cognitive capacities of people with SMIs are usually impaired; however, their relationship with frailty or social functioning have not been studied to date. The current study aimed to determine if GS is a valid predictor of changes in cognitive performance and social functioning in patients with type-2 diabetes mellitus and SMIs. METHODS: Assessments of social functioning, cognitive performance, and GS (measured with an electronic dynamometer) were conducted in 30 outpatients with type 2 diabetes mellitus, 35 with major depressive disorder, 42 with bipolar disorder, 30 with schizophrenia, and 28 healthy controls, twice during 1-year, follow-up period. Descriptive analyses were conducted using a one-way analysis of variance for continuous variables and the chi-squared test for categorical variables. Differences between groups for the motor, cognitive, and social variables at T1 and T2 were assessed using a one-way analysis of covariance, with sex and age as co-variates (p < 0.01). To test the predictive capacity of GS at baseline to explain the variance in cognitive performance and social functioning at T2, a linear regression analysis was performed (p < 0.05). RESULTS: Predictive relationships were found among GS when implicated with clinical, cognitive, and social variables. These relationships explained changes in cognitive performance after one year of follow-up; the variability percentage was 67.7%, in patients with type-2 diabetes mellitus and 89.1% in patients with schizophrenia. Baseline GS along with other variables, also predicted changes in social functioning in major depressive disorder, bipolar disorder, and schizophrenia, with variability percentages of 67.3, 36, and 59%, respectively. CONCLUSION: GS combined with other variables significantly predicted changes in cognitive performance and social functioning in people with SMIs or type-2 diabetes mellitus. Interventions aimed to improve the overall physical conditions of patients who have poor GS could be a therapeutic option that confers positive effects on cognitive performance and social functioning.