Brain Aging in Patients with Phenylketonuria – a Longitudinal Study
Description: Background: Historically, the primary goal in managing phenylketonuria (PKU) has been to prevent severe and irreversible intellectual disability, as well as to address nutritional deficiencies that could lead to growth impairments or intellectual decline. Since the introduction of neonatal PKU screening in the mid-1960s, early treatment during childhood with low phenylalanine diet and/or pharmacological interventions have been effective and prevent from severe long-term sequelae. However, concerns persist that insufficient treatment during adulthood may cause subtle and, over time, possibly increasing cognitive and brain alterations. Recently, the first generation of early-treated patients has reached mid-adulthood. Hence, there is an urgent need to understand how PKU and metabolic control impacts cognitive and brain aging and vice versa. Our preliminary cross-sectional findings suggest that brain aging trajectories may diverge significantly between patients with PKU and healthy controls in mid adulthood. Until now, no comprehensive research has longitudinally tracked brain aging in patients with PKU through MRI markers and their correlation with cognition, metabolic control, and cardiometabolic risk factors. The “brain age” approach enables the identification of individual health characteristics and risk patterns for age-related changes. In addition, the evaluation of brain age in addition to the chronological age allows for the development and monitoring of personalized neuroprotective treatments and interventions. Advancing our understanding of disease progression during aging in patients with PKU and identifying strategies for preventing potential harm later in life is of utmost importance for patient’s well-being and clinical practice and through this, follows the WHO’s brain health plan.Aims: This longitudinal study will, for the first time, investigate the trajectory of brain aging relative to chronological aging across early and middle adulthood in individuals with PKU. Data collected in our previous SNSF study (Nr 192706; 184453) will serve as baseline data and will allow the examination of brain health by means of brain age modeling. The association between brain age trajectories and cognitive performance, metabolic control, and cardiometabolic risk factors will be studied to disentangle risk patterns of accelerated brain aging in patients with a rare disease. Methods: Thirty early-treated adults with classical PKU and 30 age-, sex-, and IQ-matched healthy controls will undergo two identical assessments five years apart to evaluate cognitive function, mood, quality of life, metabolic parameters, and brain structure and function using MRI (timepoint 1: 2019–2022; age range 19–48 y, timepoint 2: 2024–2027). A well-established technique used in different clinical samples will be employed to estimate biological brain age relative to chronological age (“Brain Age Gap”). Additionally, regional changes in gray matter, brain connectivity (diffusion tensor imaging, DTI), and cerebral blood flow (arterial spin labeling, ASL) will be assessed longitudinally to depict cerebral aging trajectories across MRI sequences and brain regions. Advanced statistical analyses will associate the Brain Age Gap relative to cognition and metabolic control.Relevance of the study: This study will show whether and how the brain aging trajectory is accelerated in patients with PKU and will determine the functional relevance of brain aging with respect to cognitive performance and metabolic control (i.e. Phenylalanin levels). Our results will enable personalized early detection of deviations in the aging trajectory and provide better prognostic guidance for our first mid-aged patients with PKU. The benefits will extend beyond the PKU population and encompass a broader understanding of age-related brain changes in patient populations at risk for altered aging trajectories.
Amount: CHF 529,600
Funding type: research
Funder scheme: Project funding
Start date: 2024-10-01
End date: 2027-09-30
Investigator: Everts, Regula
Institution: University of Berne – BE
Funded outputs count: 1
Funder award ID: 10002244
OpenAlex ID: G7219315409