Clinical trial NCT05298891: Hypoproteic Diet in Acromegaly
Official title: Deciphering the Role of a Low Protein Diet in Disease Control in Acromegalic Patients
Study type: INTERVENTIONAL
Overall status: NOT_YET_RECRUITING
Phase: NA
Conditions: Acromegaly
Lead sponsor: Azienda Ospedaliero Universitaria Maggiore della Carita
Sponsor class: OTHER
First posted: 2022-03-28
Enrollment: 12
Sex: ALL
Minimum age (years): 18
Maximum age (years): 65
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: TREATMENT

Brief summary: Since protein and AAs are master regulator of GH and IGF-I secretion, we hypothesized that a low protein diet could reduce GH and IGF-I levels in acromegalic patients in addition to conventional therapy. Furthermore, we aim to explore metabolomic, microbiota, and micro-vesicle fingerprints of GH hypersecretion during conventional therapy and after a low protein diet

Detailed description: Nutrients are crucial modifiers of the GH/IGF-I axis. In particular, a close cross-talk between proteins and amino acids (AAs) and GH/IGF-I secretion exists.

Both AAs and proteins affect GH secretion. AAs stimulate GH secretion upon oral administration, with different potency among studies, being the combination of arginine and lysine the most powerful. Soy proteins also stimulate GH secretion when ingested either as hydrolysed proteins or free AAs. Furthermore, the acute GH response to AAs ingestion may be influenced by the daily amount of dietary protein/AAs consumption: diets high in proteins apparently increase basal GH levels.

AAs and proteins have a positive effect on IGF-I secretion as well. In general, high levels of proteins, especially animal and dairy proteins, and consumption of branched chain amino acids (BCAAs) increase serum IGF-I levels.

Considering pathological GH conditions, metabolomic analysis of acromegalic patients suggests that the main metabolic fingerprint of GH hypersecretion is a reduction in BCAAs, related to the disease activity. Moreover, there is evidence that GH, rather than IGF-I, is the main mediator of such metabolic fingerprint, which may be related to increased uptake of BCAAs by the muscles, increased gluconeogenesis, and raised consumption of BCAAs.

Thus, in acromegaly, a tailored diet is a further strategy that may contribute to blunt GH/IGF-I secretion. Indeed, some authors recently suggested that "personalized" or "precision" nutrition in some conditions and diseases could have an impact on their phenotype, combining dietary recommendations with individual's genetic makeup, metabolic and microbiome characteristics, and environment. However, studies on precision nutrition in acromegaly are still in a neonatal era.

Eligibility criteria: Inclusion Criteria:

* Age 18/65
* Diagnosis of Acromegaly
* In therapy with somatostatin analogues

Exclusion Criteria:

* pregnancy or lactation
* alchool or drugs abuse
* cancer
* Hematological diseases

Primary outcomes:
measure: Change in disease related hormones
timeFrame: Change from Baseline GH, IGF-1, IGFBP1, IGFBP3 blood levels at 15 days, 30 days, 45 days, 60 days
Secondary outcomes:
measure: Change in weight
timeFrame: Change from Baseline BMI at 15 days, 30 days, 45 days, 60 days
measure: Change in body circumferences
timeFrame: Change from Baseline circumferences at 15 days, 30 days, 45 dyas, 60 days
measure: Change in metabolic control
timeFrame: Change from Baseline lipid profile at 15 days, 30 days, 45 days, 60 days
measure: Change in metabolic control
timeFrame: Change from Baseline lipid profile at 60 days
measure: Change in kidney profile
timeFrame: Change from Baseline Serum Creatinin at 15 days, 30 days, 45 days, 60 days
measure: Change in liver profile
timeFrame: Change from Baseline Serum Creatinin at 15 days, 30 days, 45 days, 60 days
measure: Change in uric acid
timeFrame: Change from Baseline uric acid in blood at 15 days, 30 days, 45 days, 60 days
measure: Change in body composition
timeFrame: Change from Baseline fat mass% at 60 days
measure: Change in body composition
timeFrame: Change from Baseline fat mass% at 60 days
measure: Change in blood count
timeFrame: Change from Baseline blood count at 15 days, 30 days, 45 days, 60 days
measure: Change in microbiota
timeFrame: Change from Baseline of prevalence of microbiota phyla at 15, 30 days, 45 days, 60 days
measure: Change in omics profile
timeFrame: Change from Baseline omic profile of stools at 15, 30 days, 45 days, 60 days
measure: Change in omics profile
timeFrame: Change from Baseline omic profile of stools at 15, 30 days, 45 days, 60 days
measure: Change in microvesicles
timeFrame: Change from Baseline microvesicles levels at 15, 30 days, 45 days, 60 days
measure: Change in microvesicles
timeFrame: Change from Baseline microvesicles levels s at 15, 30 days, 45 days, 60 days
measure: Change in basal metabolic rate
timeFrame: Change from Baseline basal metabolic rate at 60 days
Other outcomes:
Locations:
city: Novara
country: Italy
facility: : Italy Pediatric Endocrine Service of AOU Maggiore della Carità of Novara; SCDU of Pediatrics, Department of Health Sciences, University of Eastern Piedmont
Study officials:
References:
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