São Paulo T21 Birth Cohort Study: longitudinal study of health and development of children with Down Syndrome in the city of São Paulo

• Grant number: 22/12022-8
• Support Opportunities: Research Grants - Young Investigators Grants
• Start date: September 01, 2023
• End date: August 31, 2028
• Field of knowledge: Health Sciences - Medicine - Maternal and Child Health
• Agreement: Instituto Jô Clemente
• Principal Investigator: Fábio Bertapelli
• Grantee: Fábio Bertapelli
• Host Institution: Instituto Jô Clemente (IJC). São Paulo , SP, Brazil
• Associated researchers: Alexandre Archanjo Ferraro ; Gabriela Arantes Wagner ; Gary R. Cutter ; Leticia Maria Santoro Franco Azevedo Soster ; Michelle Caroline Fernandes ; Stamatis Agiovlasitis
• Associated scholarship(s): 25/07263-4 - Accelerometry protocol for determining levels of physical activity of mothers and children with down syndrome: Sao Paulo T21 Cohort, BP.IC; 24/10114-8 - Technical Training São Paulo T21 Cohort: Image & Processing database, BP.TT; 24/05098-3 - Breastfeeding trajectories in children with Down syndrome aged 0 to 6 months: Sao Paulo T21 Cohort, BP.TT; + associated scholarships 23/18099-5 - The development of the T21 Health and Development Checklist (CHECK-T21) for monitoring essential care for mothers and children with Down syndrome: São Paulo T21 Cohort, BP.TT; 23/17021-2 - São Paulo T21 Cohort technical training: Normative Growth Standards, BP.TT; 23/17282-0 - São Paulo T21 Birth Cohort Technical Training: SAMPA-T21 Electronic Database, BP.TT; 23/18050-6 - São Paulo T21 Cohort Technical Training: Support and Development Center, BP.TT; 23/13038-8 - São Paulo T21 Birth Cohort Study: longitudinal study of health and development of children with Down syndrome in the city of São Paulo, BP.JP - associated scholarships

Abstract

Down syndrome (DS) is a genetic condition affecting multiple body systems. Neurodevelopment disorders, growth faltering, heart defects, obesity, sleep disorders, motor delay and inactivity are among the many health conditions associated with DS. However, several challenges are related to the study of these characteristics, including their prevalence, epidemiology, and patterns. First, there is a scarcity of information related to health and development of children with DS in low- and middle-income countries (LMICs). Second, there is limited evidence about the health and development of children with DS from prospective birth cohorts, especially in LMICs. Third, the identification of early multi-domain functional phenotypes, including neurodevelopment, growth, sleep, nutrition, physical activity, and motor trajectories is scarce in children with DS before three years of age, limiting early characterization of DS children most at risk for adverse outcomes. Our study will identify and characterize the early phenotypes of high, moderate, and low functionality through prospectively evaluating the health, growth, nutrition, sleep, physical activity, neurodevelopment, and motor functions in all children with DS born between August 1, 2024, and July 31, 2025. These phenotypes will be used to guide clinical risk prediction and enable optimization of limited healthcare resources for maximal benefit by targeting these appropriately to different phenotypes of functional severity. Comprehensive data for health and brain function profiling will be undertaken between birth and 36 months of age. This will include data on prenatal and perinatal morbidity, birth and neonatal outcomes, anthropometry including measures of fat and lean mass (using skinfold and Bod Pod measurements), breastfeeding, infant and child morbidity, immunization status and comprehensive neuropsychomotor (Neo-NBA, OX-NDA, and INTER-NDA tests), vision (Cardiff tests), auditory (auditory brain stem evoked potentials) functional assessments, daily and nocturnal quantification of movements, and sleep events, including latency, sleep duration, awakenings, and efficiency (using triaxial accelerometers and polysomnography) at 0, 1 and 2 years of age. Using comprehensive health and brain function profiling and multiple statistical techniques with machine learning, we will (1) construct functional trajectories for our cohort (2) identify high, moderate, and low function phenotypes and (3) identify key drivers of risk and resilience. Our findings will generate important data to guide early clinical prediction of high risk phenotypes, enable early targeting of interventions. Our analysis will also help to identify novel targets for intervention within the first 1000 days of life for DS children. By adopting this approach, our study will be the first comprehensive cohort enabling both risk prediction and therapeutic target identification specific to DS children in LMICs. (AU)