Jun Lu1, Dech Dokpuang1, Rinki Murphy2, Lindsay Plank2, John Zhiyong Yang1, Reza Nemati3, and Kevin Haokun He4
1School of Science, Auckland University of Technology, Auckland, New Zealand, 2School of Medicine, University of Auckland, Auckland, New Zealand, 3Canterbury Health Laboratories, Canterbury District Health Board, Christchurch, New Zealand, 4Saint Kentigern College, Auckland, New Zealand
Synopsis
Pancreatic fat has been reported to be closely
related to type 2 diabetes risk, hence is the subject of our investigation in a
clinical trial. Pancreatic fat changes before and after a 12-week intermittent fasting programme with or without
daily probiotic were determined using
magnetic resonance imaging (MRI). Two-point Dixon protocol was used to scan
patients and manual image-processing method was used to quantify the fat. A
significant reduction in pancreatic fat was observed after intermittent
fasting, while addition of probiotic did not increase pancreatic fat reduction.
Introduction
Accumulation of
ectopic fat in the pancreas has been linked to type 2 diabetes risk 1,2,3. Probiotic supplementation has been reported to be effective in
glycemic control 4. Intermittent fasting has been shown to
have positive effect on the control and prevention of type 2 diabetes,
improving several metabolic indices including body weight, fasting glucose and
postprandial variability 5. However, the effect of those interventions on pancreatic fat, which is a key
risk factor of type 2 diabetes, has not been thoroughly investigated. The most accurate ectopic fat measurement is via
magnetic resonance (MR) technique6-9. In this study, we conducted a
clinical trial to study the effect of intermittent fasting with or without a probiotic supplement on pancreatic fat, using
MRI as a tool for pancreatic fat quantification. The objective of this project
was to study pancreatic fat changes in relation to interventions.Methods
This is a parallel randomised, placebo-controlled trial to test the
treatment effect of daily L rhamnosus HN001 (6x109
cfu)/placebo capsule with intermittent (5:2) fasting in New Zealand adults with
prediabetes. Men and women aged over 18 years of age with prediabetes defined
as HbA1c between 40-49mmol/mol and BMI > 35 were recruited. Exclusion
criteria are known diabetes or pregnancy, medical conditions or medications
likely to affect the assessment for diabetes. In total, 24 patients were
recruited. Twelve each were assigned to the intermittent fasting with placebo
group and the intermittent fasting with probiotic group. Patients followed the
prescribed dietary programme for 12 weeks. They were MR-scanned before and
after the dietary intervention.
Each patient was
scanned for the entire abdomen by a 3.0 Tesla Siemens MR scanner. A 3D dual
gradient-echo sequence acquired water/fat images in one acquisition using a
2-point Dixon technique. T1-weighted spin echo pulse sequence was used with:
TR, 6.5 msec, TE, 2.4/4.8 msec, flip angle, 12 degrees, matrix, 256 x 128, and
0.7 excitation. The pancreas was scanned using a similar protocol, with
12-second breath hold and a number of 5.0 mm slices were planned across the
pancreas. For fat volume determination in pancreas, two methods were used. The first method used two
independent operators to process the images manually in ImageJ. The coverage of
the entire pancreas including slices and boundaries in water-only and water-fat
images was determined, and volume calculated. Then, the fat volume within all
above-determined pancreas slices was calculated in the fat-only images and the
fat volume percentage of the entire pancreas was deduced. A second method was
employed to validate the results of the first method which is termed MR-OPSY method 10. Three 100 mm2 regions
of interest (ROIs) were selected in head, body and tail of one slice of pancreas image. Then the fat area against the
ROI area was determined in the fat-only images, which represents the percentage
of fat in the entire pancreas. Results
Ten
patients completed MRI study in the intermittent fasting with placebo group and
twelve patients completed MRI scans in the intermittent fasting with probiotic
group. Figure 1 shows an example of fat determination in pancreas with two
methods. Figure 2 shows significant Pearson’s correlation of the pancreatic fat
percentage numbers (44 pairs of number) determined by two methods (r value
0.9235), as well as the resulting pancreatic fat change of the 22 patients
calculated by two methods (r value 0.7016). Both intermittent fasting for 12
weeks with and without probiotics produced significant pancreatic fat reduction
(p = 0.0009 and 0.0027, respectively, Figure 3). However, there is no
significant difference of pancreatic fat loss between the two groups (p =
0.2269, Figure 4).Discussion
This
is the first study to assess changes in pancreatic fat using MRI in prediabetes
patients on intermittent fasting with probiotic or placebo supplement for 12
weeks. The two post-scan image processing method appears to correlate well in
general, providing similar outcomes. The MROPSY method is easy to operate and
involves less calculation. The whole pancreas analysis method is more labour
intensive. However, the ROI selections in images from before and after
intervention may not be near identical. This may introduce errors because of
inhomogeneity of fat distribution in the pancreas, especially when sample size
is small. Our study shows that intermittent fasting can reduce pancreatic fat
significantly, which is a key risk factor of type 2 diabetes, in a relatively
short period of time. The addition of probiotics, on the other hand, does not
add any extra benefit in terms of pancreatic fat reduction. Conclusion
MRI method is a useful tool to measure
pancreatic fat change in clinic, which may provide type 2 diabetes risk
indication. Lifestyle change, such as intermittent fasting, can definitely
reduce the type 2 diabetes risk in obese and prediabetic patients. Probiotics
on the other hand, may not provide direct benefit to type 2 diabetes risk
reduction, particularly in terms of pancreatic fat reduction.Acknowledgements
This research was supported by a grant from Health Research Council of New ZealandReferences
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