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NCT Number: NCT06969209

Brain Aging in Phenylketonuria

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 a low phenylalanine diet or pharmacological interventions have been effective and prevent 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 impact cognitive and brain aging and vice versa. The investigators 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. The evaluation of brain age in addition to the chronological age allows for the development and monitoring of personalized neuroprotective treatments and interventions. Advancing the investigators 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 patients' well-being and clinical practice and, through this, follows the WHO's brain health plan.

Study 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 compared to healthy controls. Data collected in the investigators previous SNSF study (Nr 192706; 184453) will serve as baseline data and 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.

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., phenylalanine levels). This is one of the first studies to closely examine long-term brain and cognitive changes in PKU during early and mid-adulthood. Its findings could provide valuable insights into the long-term effects of PKU on brain structure and aging processes. Furthermore, the results may support the development of future treatment strategies and improve the quality of life for adults with PKU.

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Key information

Conditions

Phenylketonuria (PKU) Amino Acid Metabolism, Inborn Errors Brain Diseases Brain Diseases, Metabolic Brain Diseases, Metabolic, Inborn Central Nervous System Diseases Congenital, Hereditary, and Neonatal Diseases and Abnormalities Disease Attributes Genetic Diseases, Inborn Metabolic Diseases Metabolism, Inborn Errors Nervous System Diseases Nutritional and Metabolic Diseases Pathologic Processes Pathological Conditions, Signs and Symptoms Phenylketonurias Rare Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

University Hospital Inselspital, Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism (UDEM)

Bern, 3010, Switzerland

Location status: Recruiting

Location contact

Regula Everts, Prof. Dr. phil.

CONTACT

[email protected]

+41 31 63 2 84 97

About this study

Detailed Research Plan:

The investigators' preliminary findings suggest that patients with PKU might show altered aging trajectories compared to controls. The present study will investigate the aging trajectory in patients with PKU and its association with cognitive and metabolic aging over a 5-year time period. The investigators will use the well-established "Brain Age Gap" metric, which defines the biological brain age relative to the chronological age across different brain regions. Based on the investigators' preliminary and published results the following hypotheses are postulated:

A) There is accelerated brain aging in certain brain regions (as measured with an increasing Brain Age Gap) over a 5-year follow-up period in patients with PKU.

B) The Brain Age Gap relates to cognitive performance, blood-Phe levels, and other metabolic parameters in patients with PKU.

C) In patients, age-related changes in gray matter metrics (prefrontal cortical thickness), white matter microstructure, and cerebral blood flow will be more pronounced over the 5-year follow-up period than in controls.

D) Patients' cognitive performance decreases more strongly over the 5-year follow-up period in sustained attention and cognitive flexibility than controls' cognitive performance.

E) In patients, there is a relationship between changes in structural and functional brain characteristics and changes in cognitive performance and metabolic parameters.

Study procedure: The study procedure will mimic the baseline assessment as closely as possible. All patients will be asked again to take part in this longitudinal study. Participants will therefore be the same as at Time Point 1 (TP1) which was performed between 2019 and 2022, involving 30 early-treated adult patients with PKU (13 females, median age = 35.5 years, IQR = 12.3, age range = 19-48 years) and 59 healthy age-, sex-, and IQ-matched controls (33 males, 26 females, median age = 30.0 years, IQR = 11.0, age range = 18-53 years). TP2 (Time point 2, 5-year follow-up) will take place between 2024 and 2027, with the same assessments and methods. All participants will undergo identical assessments five years apart to evaluate cognitive function, mood, quality of life, metabolic parameters, and brain structure and function using MRI. Patients with PKU and healthy controls will undergo the same study procedure: after an overnight fasting period, a blood sample will be drawn early in the morning (6-8 am) followed by a DXA (Dual Energy X-ray Absorptiometry). After this, the 1-hour MRI will be performed under the guidance of the team from the Institute of Diagnostic and Interventional Neuroradiology. After a break, which includes a low-protein snack, a 2-hour neuropsychological assessment will be performed by a neuropsychologist. All assessments will take place at the University Hospital Inselspital Bern.

Brain Age Gap: A well-established technique used in different clinical samples will be employed to estimate biological brain age relative to chronological age, the so called "Brain Age Gap". Additionally, regional changes in gray matter, brain connectivity and cerebral blood flow 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. Machine learning models will be used to estimate brain age based on MRI-derived measures. For each participant, an estimate of the Brain Age Gap (predicted brain age minus chronological age), indicating the degree of brain maintenance will be calculated using XGBoost. XGBoost uses gradient tree boosting based on 1118 features to predict the Brain Age Gap. These features are extracted using the open-source software FreeSurfer. The features consist of thickness, area, and volume measurements from a multimodal parcellation of the cerebral cortex, cerebellum, and subcortex.

Statistical Analyses:

Changes in global and regional Brain Age Gaps between baseline (TP1) and the 5-year follow-up (TP2) in patients and controls will be evaluated with linear mixed models using restricted maximum likelihood (REML) estimation (hypothesis A). These models will include global and regional Brain Age Gaps as dependent variables, time, group, and the interaction between time and group as a fixed effect, while age and sex will be incorporated as covariates. Participant ID will be modeled as a random effect (intercept) to account for within-subject variance. The linear mixed modeling approach will also be applied to the cognitive and metabolic data. To assess the associations between Brain Age Gap estimates, cognitive performance, and metabolic parameters, linear models and raw values, again with BAG as dependent variable and cognition and metabolic parameters as independent variables will be calculated (hypothesis B). Age-related changes in cerebral markers (structural gray and white matter metrics, cerebral blood flow) in patients and controls will be assessed with the same linear mixed model approach used for hypothesis A, replacing Brain Age Gaps with these cerebral markers as dependent variables (hypothesis C). Likewise, changes in cognitive performance in patients and controls will be evaluated with linear mixed models (hypothesis D). Finally, the relationship between changes in cerebral markers, cognitive performance, and metabolic data will be investigated using the same model approach as in hypothesis B, with changes in cerebral markers serving as dependent variable and cognition and metabolic parameters as independent variables (hypothesis E). Statistical significance will be determined at a threshold of p < .05, with corrections for multiple comparisons applied via the false discovery rate (FDR) procedure.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Patients with PKU

Inclusion criteria

  • Participation in PICO-Study and/or:
  • PKU diagnosed after a positive newborn screening
  • Treatment with Phe-restricted diet starting within the first 30 days of life
  • Age ≥18 years
  • Written informed consent

Exclusion criteria

  • Patients with PKU not following a Phe-restricted diet within 6 months before the study
  • Phe concentration above 1600 µmol/L within 6 months before the study
  • Concomitant disease states suspected to significantly affect primary or secondary outcomes
  • Women who are pregnant or who are breast feeding
  • Conditions interfering with MRI such as magnetic (metallic) particles in the skull or brain, cardiac pacemaker, deep brain stimulators, cochlear implant, braces or permanent retainers

Healthy controls

Inclusion criteria

  • Age ≥18 years
  • Written informed consent

Exclusion criteria

  • Concomitant disease states suspected to significantly affect primary or secondary outcomes
  • Women who are pregnant or who are breast feeding
  • Inability to follow the procedures of the study, e. g. due to language problems (lack of fluency in German or French), psychological disorders, dementia, etc. of the participant
  • Conditions interfering with MRI such as magnetic (metallic) particles in the skull or brain, cardiac pacemaker, deep brain stimulators, cochlear implant, braces or permanent retainers

Treatment and study plan

Primary outcomes

  1. Brain Age Gap

    Time frame: Time Point 2 (5-year follow-up)

    Defines the biological brain age relative to the chronological age across different brain regions. Machine learning models will be used to estimate brain age based on MRI-derived measures. For each participant, an estimate of the Brain Age Gap (predicted brain age minus chronological age, indicating the degree of brain maintenance) will be calculated using XGBoost. XGBoost uses gradient tree boosting based on 1118 features to predict the Brain Age Gap. These features are extracted using Freesurfer. The features consist of thickness, area, and volume measurements from a multimodal parcellation of the cerebral cortex, cerebellum, and subcortex. Possible changes in the Brain age gap will be evaluated by comparing the baseline measurement with the 5 year follow up.

  2. Sustained Attention

    Time frame: Time Point 2 (5-year follow-up)

    Changes in sustained attention over 5-years are assessed with the respective subtest "sustained attention" of the Test of Attentional Performance (TAP) in patients with PKU and healthy controls. In this subtest, stimuli with varying features (color, shape, size, filling) appear on a monitor. A target stimulus matches the previous one in one of two predefined dimensions (same shape or same color). Sustained attention is measured in milliseconds, with higher values showing slower reaction time to target stimulus.

  3. Cognitive flexibility

    Time frame: Time Point 2 (5-year follow-up)

    Changes in cognitive flexibility over 5-years are assessed using the fourth condition "inhibition/switching" of the color-word interference test of the Delis-Kaplan Executive Function System (D-KEFS) in patients with PKU and healthy controls. Time is measured in seconds with higher completion time indication worse performance in cognitive flexibility.

  4. Plasma concentration of Phe

    Time frame: Time Point 2 (5-year follow-up)

    Plasma Phenylalanine (Phe) concentrations are measured in patients with PKU

  5. Diffusion tensor imaging (DTI)

    Time frame: Time Point 2 (5-year follow-up)

    DTI is used to assess white matter integrity in patients with PKU and healthy controls.

  6. Arterial Spin Labeling (ASL)

    Time frame: Time Point 2 (5-year follow-up)

    ASL is used to assess cerebral blood flow in patients with PKU and healthy controls.

Secondary outcomes

  1. Resting-state fMRI

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    Resting-state fMRI will be used to assess functional connectivity in certain brain regions in patients with PKU and healthy controls

  2. FLAIR-sequence

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    The T2-fluid-attenuated inversion recovery (Flair) will be used to measure white matter lesions in patients with PKU and healthy controls.

  3. MPRAGE

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    A Magnetization Prepared-RApid Gradient Echo (MPRAGE) will be used to obtain high-resolution structural T1-weighted images in patients with PKU and healthy controls.

  4. General intelligence

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    General intelligence will be evaluated using four subtests (vocabulary, arithmetics, symbol search, and matrix reasoning) of the Wechsler Adult Intelligence Scale Fourth Edition (WAIS-IV) in patients with PKU and healthy controls. Average IQ ranges from 85 - 115. Scores above indicate above average IQ, scores below indicate below average IQ.

  5. Processing speed

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    Processing speed will be assessed using the first and second condition of the Stroop test (naming and reading speed; D-KEFS) in patients with PKU and healthy controls. Time is measured in seconds with higher completion time indication worse performance in cognitive flexibility.

  6. Working memory

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    Working memory will be evaluated using the subtest n-back of the computerized test of attentional performance (TAP) in patients with PKU and healthy controls.

  7. Inhibition

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    Inhibition will be measured using the third condition of the Stroop test of the D-KEFS in patients with PKU and healthy controls.

  8. Design fluency

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    Design fluency, the initiation and fluency of generating visual patterns, will be examined using the subtest "design fluency" of the D-KEFS in patients with PKU and healthy controls.

  9. Motor control and speed

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    Fine motor control and fine motor speed will be evaluated using the Purdue Pegboard, which will help to determine manual dexterity and bimanual coordination in patients with PKU and healthy controls.

  10. Verbal fluency

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    Verbal fluency, including letter fluency, will be assessed using the respective subtest of the D-KEFS in patients with PKU and healthy controls.

  11. Body fat

    Time frame: Time Point 2 (5-year follow-up)

    Body fat, including total fat content and visceral fat, will be measured using the Lunar iDXA system (GE Medical Systems, Madison, USA) and Encore software version 18 in patients with PKU and healthy controls. Percentages of fat will be calculated and fat content will be transferred into z-scores. Visceral fat will be measured in gram. A fat mass index will also be calculated.

  12. Bone density

    Time frame: Time Point 2 (5-year follow-up)

    Bone density for whole-body, femur, and spine densitometry, will be measured using the Lunar iDXA system (GE Medical Systems, Madison, USA) and Encore software version 18 in patients with PKU and healthy controls. Measurements will all be transferred into t-scores and z-scores.

  13. Body Mass Index

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    To asses cardiovascular risk factors, the Body Mass Index (BMI) will be measured in kg/m² in patients with PKU and healthy controls.

  14. Tyrosine

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    To asses the amino acid profile, plasma concentrations of tyrosine (Tyr) will be measured through a blood sample following an 8-12 hour overnight fast in patients with PKU and healthy controls. High-performance ion-exchange chromatography (HPLC) coupled with post-column photometric detection of ninhydrin-derivatized amino acids will be employed for amino acid quantification.

  15. Tryptophan

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    To asses the amino acid profile, plasma concentrations of tryptophan (Trp) will be measured through a blood sample following an 8-12 hour overnight fast in patients with PKU and healthy controls. High-performance ion-exchange chromatography (HPLC) coupled with post-column photometric detection of ninhydrin-derivatized amino acids will be employed for amino acid quantification.

  16. Dry blood samples

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    To asses the amino acid profile, dry blood samples will be collected twice weekly during the month before (7 dry blood filter cards in total) and at the 5-year follow-up in patients with PKU.

  17. Total cholesterol

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    To asses cardiometabolic risk factors associated with the Brain Age Gap and accelerated brain aging, total cholesterol will be measured through a blood sample in patients with PKU and healthy controls.

  18. LDL cholesterol

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    To asses cardiometabolic risk factors associated with the Brain Age Gap and accelerated brain aging, LDL (low-density lipoprotein) cholesterol will be measured through a blood sample in patients with PKU and healthy controls.

  19. HDL cholesterol

    Time frame: Time Point 2 (5-year follow-up)

    To asses cardiometabolic risk factors associated with the Brain Age Gap and accelerated brain aging, HDL (high-density lipopro-tein) cholesterol will be measured through a blood sample in patients with PKU and healthy controls.

  20. Triglycerides

    Time frame: Time Point 2 (5-year follow-up)

    To asses cardiometabolic risk factors associated with the Brain Age Gap and accelerated brain aging, Triglycerides will be measured through a blood sample in patients with PKU and healthy controls.

  21. Apolipoprotein B (ApoB)

    Time frame: Time Point 2 (5-year follow-up)

    To asses cardiometabolic risk factors associated with the Brain Age Gap and accelerated brain aging, Apolipoprotein B (ApoB) will be measured through a blood sample in patients with PKU and healthy controls.

  22. Lipoprotein (a)

    Time frame: Time Point 2 (5-year follow-up)

    To asses cardiometabolic risk factors associated with the Brain Age Gap and accelerated brain aging, Lipoprotein (a) (Lp (a)) will be measured through a blood sample in patients with PKU and healthy controls.

  23. Fasting Glucose

    Time frame: Time Point 2 (5-year follow-up)

    To asses cardiometabolic risk factors associated with the Brain Age Gap and accelerated brain aging, Fasting Glucose will be measured through a blood sample in patients with PKU and healthy controls.

  24. HbA1c

    Time frame: Time Point 2 (5-year follow-up)

    To asses cardiometabolic risk factors associated with the Brain Age Gap and accelerated brain aging, HbA1c will be measured through a blood sample in patients with PKU and healthy controls.

  25. High-sensitivity C-reactive protein

    Time frame: Time Point 2 (5-year follow-up)

    To asses cardiometabolic risk factors associated with the Brain Age Gap and accelerated brain aging, high-sensitivity C-reactive protein (hs-CRP) will be measured through a blood sample in patients with PKU and healthy controls.

  26. Blood pressure

    Time frame: Time Point 2 (5-year follow-up)

    To asses cardiovascular risk factors associated with the Brain Age Gap and accelerated brain aging , systolic and diastolic blood pressure will be measured in mmHg in patients with PKU and healthy controls.

  27. Heart rate

    Time frame: Time Point 2 (5-year follow-up)

    To asses cardiovascular risk factors associated with the Brain Age Gap and accelerated brain aging heart rate will be measured in bpm in patients with PKU and healthy controls.

  28. Body Mass Index

    Time frame: Time Point 2 (5-year follow-up)

    To asses cardiovascular risk factors associated with the Brain Age Gap and accelerated brain aging Body Mass Index (BMI) will be measured in kg/m2 in patients with PKU and healthy controls.

  29. Total tau

    Time frame: Time Point 2 (5-year follow-up)

    To assess brain age related biomarkers, total tau (t-tau) will be measured through a blood sample in patients with PKU and healthy controls.

  30. Total tau and phosphorylated tau

    Time frame: Time Point 2 (5-year follow-up)

    To investigate blood markers shown to reflect brain aging, total tau (t-tau) and phosphorylated tau (p-tau) will be measured through a blood sample in patients with PKU and healthy controls.

  31. Neurofilament light chain

    Time frame: Time Point 2 (5-year follow-up)

    To investigate blood markers shown to reflect brain aging, neurofilament light chain (NfL) will be measured through a blood sample in patients with PKU and healthy controls.

  32. Myeloid Cells 2

    Time frame: Time Point 2 (5-year follow-up)

    To investigate blood markers shown to reflect brain aging, Myeloid Cells 2 (TREM2) will be measured through a blood sample in patients with PKU and healthy controls.

  33. Glial fibrillary acidic

    Time frame: Time Point 2 (5-year follow-up)

    To investigate blood markers shown to reflect brain aging, glial fibrillary acidic Protein (GFAP) will be measured through a blood sample in patients with PKU and healthy controls.

  34. CC-chemokine ligand 11 and C-C Motif Chemokine Ligand 2

    Time frame: Time Point 2 (5-year follow-up)

    To investigate blood markers shown to reflect brain aging, CC-chemokine ligand 11 (CCL11) and C-C Motif Chemokine Ligand 2 (CCL2) will be measured through a blood sample in patients with PKU and healthy controls.

  35. Albumin

    Time frame: Time Point 2 (5-year follow-up)

    To investigate blood markers shown to reflect brain aging, Albumin in plasma (BCP-method) will be measured through a blood sample in plasma in patients with PKU and healthy controls.

Other outcomes

  1. Mood

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    Mood will be examined using the short form of the Profile of Mood States (POMS) in patients with PKU and healthy controls.

  2. Depression

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    Depression will be identified using Beck's Depression Inventory (BDI-II) in patients with PKU and healthy controls. The total score indicates severity, ranging from 0 (no depression) to 63 (severe depression).

  3. PKU Quality of Life

    Time frame: Time Point 1 (Baseline) and Time Point 2 (5-year follow-up)

    The questionnaire PKU quality of life (PKUQOL) will be used to assess the physical, emotional, and social impact of PKU in patients with PKU. The questionnaire allows the calculation of 35 domain scores across four modules (symptoms, PKU in general, supplement administration, and dietary protein restriction). Domain scores range from 1 to 100 whereby scores ≤25 reflect little or no impact, domain scores between 26 and 50 suggest moderate impact, domain scores between 51 and 75 indicate major impact, and domain scores >75 reflect severe impact.

  4. Sleep Quality

    Time frame: Time Point 2 (5-year follow-up)

    To assess Sleep Quality the Pittsburgh Sleep Quality Index (PSQI) will be used in patients with PKU and healthy controls. The global score consists of seven component scores and ranges from 0 to 21 with higher scores indicating worse sleep quality.

  5. Stress

    Time frame: Time Point 2 (5-year follow-up)

    To assess perceived Stress the Perceived Stress Scale (PSS-10) will be used in patients with PKU and healthy controls. The total score is the sum of the subscale perceived helplessness and the inverted subscale perceived self-efficacy and ranges from 0 to 40. Higher scores indicate greater levels of stress.

  6. Resilience

    Time frame: Time Point 2 (5-year follow-up)

    To assess resilience the Connor Davidson Resilience Scale -10 (CD-RISC-10) will be used in patients with PKU and healthy controls. Scores range from 0 to 40 with higher scores indicating greater resilience.

Study contacts

Contact information is provided by the study sponsor or research team.

Regula Everts, Prof. Dr. phil.

CONTACT

[email protected]

+41 31 63 2 84 97

Sponsors and collaborators

Lead sponsor

Insel Gruppe AG, University Hospital Bern

Other

Registry information

Official study title

Brain Aging in Patients With Phenylketonuria

Important dates

Study start
2025
Primary completion
2030
Study completion
2030
First posted
May 13, 2025
Registry last updated
May 13, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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