RAFAEL DE OLIVEIRA ALVIM
Projetos de Pesquisa
Unidades Organizacionais
LIM/13 - Laboratório de Genética e Cardiologia Molecular, Hospital das Clínicas, Faculdade de Medicina
3 resultados
Resultados de Busca
Agora exibindo 1 - 3 de 3
- Metabolic syndrome alters relationships between cardiometabolic variables, cognition and white matter hyperintensity load(2019) ALKAN, E.; TAPOROSKI, T. P.; STERR, A.; SCHANTZ, M. von; VALLADA, H.; KRIEGER, J. E.; PEREIRA, A. C.; ALVIM, R.; HORIMOTO, A. R. V. R.; POMPEIA, S.; NEGRAO, A. B.; EVANS, S. L. H.Cardiometabolic risk factors influence white matter hyperintensity (WMH) development: in metabolic syndrome (MetS), higher WMH load is often reported but the relationships between specific cardiometabolic variables, WMH load and cognitive performance are uncertain. We investigated these in a Brazilian sample (aged 50-85) with (N = 61) and without (N=103) MetS. Stepwise regression models identified effects of cardiometabolic and demographic variables on WMH load (from FLAIR MRI) and verbal recall performance. WMH volume was greater in MetS, but verbal recall performance was not impaired. Age showed the strongest relationship with WMH load. Across all participants, systolic blood pressure (SBP) and fasting blood glucose were also contributors, and WMH volume was negatively associated with verbal recall performance. In non-MetS, higher HbA1c, SBP, and number of MetS components were linked to poorer recall performance while higher triglyceride levels appeared to be protective. In MetS only, these relationships were absent but education exerted a strongly protective effect on recall performance. Thus, results support MetS as a construct: the clustering of cardiometabolic variables in MetS alters their individual relationships with cognition; instead, MetS is characterised by a greater reliance on cognitive reserve mechanisms. In non-MetS, strategies to control HbA1c and SBP should be prioritised as these have the largest impact on cognition.
- Heritability of semantic verbal fluency task using time-interval analysis(2019) TAPOROSKI, T. P.; DUARTE, N. E.; POMPEIA, S.; STERR, A.; GOMEZ, L. M.; ALVIM, R. O.; HORIMOTO, R. V. R.; KRIEGER, J. E.; VALLADA, H.; PEREIRA, A. C.; SCHANTZ, M. von; NEGRAO, A. B.Individual variability in word generation is a product of genetic and environmental influences. The genetic effects on semantic verbal fluency were estimated in 1,735 participants from the Brazilian Baependi Heart Study. The numbers of exemplars produced in 60 s were broken down into time quartiles because of the involvement of different cognitive processes-predominantly automatic at the beginning, controlled/executive at the end. Heritability in the unadjusted model for the 60-s measure was 0.32. The best-fit model contained age, sex, years of schooling, and time of day as covariates, giving a heritability of 0.21. Schooling had the highest moderating effect. The highest heritability (0.17) was observed in the first quartile, decreasing to 0.09, 0.12, and 0.0003 in the following ones. Heritability for average production starting point (intercept) was 0.18, indicating genetic influences for automatic cognitive processes. Production decay (slope), indicative of controlled processes, was not significant. The genetic influence on different quartiles of the semantic verbal fluency test could potentially be exploited in clinical practice and genome-wide association studies.
- Poor sleep quality and lipid profile in a rural cohort (The Baependi Heart Study)(2019) GEOVANINI, Glaucylara Reis; LORENZI-FILHO, Geraldo; PAULA, Lilian K. de; OLIVEIRA, Camila Maciel; ALVIM, Rafael de Oliveira; BEIJAMINI, Felipe; NEGRAO, Andre Brooking; SCHANTZ, Malcolm von; KNUTSON, Kristen L.; KRIEGER, Jose Eduardo; PEREIRA, Alexandre CostaAim: To test the association between cardiometabolic risk factors and subjective sleep quality assessed by the Pittsburgh sleep quality index (PSQI), independent of obstructive sleep apnea (OSA) and sleep duration. Methods: A total of 573 participants from the Baependi Heart Study, a rural cohort from Brazil, completed sleep questionnaires and underwent polygraphy for OSA evaluation. Multivariable linear regression analysis tested the association between cardiovascular risk factors (outcome variables) and sleep quality measured by PSQI, adjusting for OSA and other potential confounders (age, sex, race, salary/wage, education, marital status, alcohol intake, obesity, smoking, hypertension, and sleep duration). Results: The sample mean age was 43 +/- 16 years, 66% were female, and mean body mass index (BMI) was 26 +/- 5 kg/m(2). Only 20% were classified as obese (BMI >= 30). Overall, 50% of participants reported poor sleep quality as defined by a PSQI score >= 5. A high PSQI score was significantly associated with higher very-low-density lipoprotein (VLDL) cholesterol levels (beta = 0.392, p = 0.012) and higher triglyceride levels (beta = 0.017, p = 0.006), even after adjustments, including the apneaehypopnea index. Further adjustments accounting for marital status, alcohol intake, and medication use did not change these findings. No significant association was observed between PSQI scores and glucose or blood pressure. According to PSQI components, sleep disturbances (beta = 1.976, p = 0.027), sleep medication use (beta = 1.121, p = 0.019), and daytime dysfunction (beta = 1.290, p = 0.024) were significantly associated with higher VLDL serum levels. Only the daytime dysfunction domain of the PSQI components was significantly associated with higher triglyceride levels (beta = 0.066, p = 0.004). Conclusion: Poorer lipid profile was independently associated with poor sleep quality, assessed by the PSQI questionnaire, regardless of a normal sleep duration and accounting for OSA and socio-economic status.