HD Research Around the World: France

franceImaging Brain Metabolic Markers at the Institut du Cerveau et de la Moelle Épinière (ICM), Paris

By: Isaac M. Adanyeguh

In addition to the well-known neurological phenotype, HD presents with non-neurological symptoms that suggest hyper-catabolism in the early stage of the disease, leading to significant weight loss1. Metabolic dysfunction is therefore a major focus of HD research and may be easily amenable to therapeutic intervention2. Our team has shown that dietary anaplerotic therapy can improve peripheral energy metabolism in HD patients3. We also emphasized the potential of non-invasive 31- phosphorus magnetic resonance spectroscopy (31P MRS) in biomarker identification3. However, a sensitive biomarker of brain energy metabolism in HD patients has yet to be identified. Our team at ICM, Hôpital Pitié- Salpêtrière in Paris, led by Prof. Alexandra Durr and Dr. Fanny Mochel, is therefore interested in identifying biomarkers that reflect brain energy metabolism that could be used in therapeutic trials in HD patients.

To identify sensitive brain metabolic markers based on the results obtained in muscle3, we recruited 15 HD patients in the early stage of HD, but who were without significant cognitive impairment, and 15 age- and sex-matched controls, as subjects for brain 31P MRS on a 3T Siemens Magnetom Trio system. We targeted the visual cortex for the single-voxel functional MRS because it is easily stimulated and has high energy metabolism (Figure 1a). It is also very close to the scalp, giving an increased sensitivity to the small surface coils. A 6 cm 31P transmit/receive surface coil (Figure 1b) was used to detect signals (free induction decays – FIDs) from the visual cortex for 4 minutes at rest (baseline), 8 minutes during visual activation, and 8 minutes after visual stimulation (recovery), while limiting signals from other brain regions. A small sphere 10 mm in diameter filled with water and placed below the coil along the coil axis helped to verify and adjust the position of the 31P coil on T1 images (Figure 1a). Visual stimulation was performed with 6 Hz red and black checkerboard flashes (Figure 1c) generated in MATLAB and projected by a video projector onto a screen at the beginning of 8 minutes of stimulation. Subjects were able to focus on the flashes with a nonmagnetic mirror mounted above their eyes.

Figure 1: a) T1-weighted image with highlighted visual cortex showing the position of the sphere filled with water. The black square shows the region used for localized 1H shimming. The dashed white line indicates the sensitive volume of the coil encompassing most of the visual cortex.

Figure 1a:
T1-weighted image with highlighted visual cortex showing the position of the sphere filled with water. The black square shows the region used for localized 1H shimming. The dashed white line indicates the sensitive volume of the coil encompassing most of the visual cortex.

Figure 1: b) The 6 cm 31P transmit/receive coil in a holder with mounted mirror used in the lab.

Figure 1b:
The 6 cm 31P transmit/receive coil in a holder with mounted mirror used in the lab.

Figure 1: c) Red and black checkerboard used for visual stimulation

Figure 1c:
Red and black checkerboard used for visual stimulation.

 

 

 

 

 

 

 

 

 

 

 

We obtained 31P spectra from our MRS protocol in the brain (Figure 2). Analysis of the 31P spectra in the time domain using jMRUI software allowed the quantification of energy metabolites ATP, Pi and PCr. The ratio of Pi/PCr was then calculated to determine the brain response to cortical activation. The Pi/PCr ratio has been linked to mitochondrial activation and it provides an index of mitochondrial oxidative regulation4. At rest, there was no significant difference in Pi/ PCr ratio between HD patients and control subjects. Visual stimulation allowed us to analyse the evolution of the Pi/PCr ratio in HD and control subjects. The Bonferroni-corrected Wilcoxon signed-rank test indicated an 11% increase in Pi/PCr ratio between rest and activation (P = 0.024), followed by a decrease between activation and recovery (P = 0.012) in controls (Figure 3). In contrast, no difference was found between the three stages for the HD group for Pi/PCr ratio (Figure 3).

Figure 2: Representative 31P spectrum obtained at 3T with well-defined high-energy phosphate metabolites from the visual cortex of a control subject.

Figure 2:
Representative 31P spectrum obtained at 3T with well-defined high-energy phosphate metabolites from the visual cortex of a control subject.

Figure 3: Pi/PCr ratio before, during and after visual stimulation of 15 HD patients and 15 age- and sex-matched controls. Bonferroni-corrected Wilcoxon signedrank test indicated increased Pi/PCr between rest and activation (p = 0.024a) followed by a decrease between activation and recovery (p = 0.012b). No change was observed in patients (p > 0.05).

Figure 3:
Pi/PCr ratio before, during and after visual stimulation of 15 HD patients and 15 age- and sex-matched controls. Bonferroni-corrected Wilcoxon signedrank test indicated increased Pi/PCr between rest and activation (p = 0.024a) followed by a decrease between activation and recovery (p = 0.012b). No change was observed in patients (p > 0.05).

 

 

 

 

 

 

 

 

 

 

 

Because the observed changes were relatively small, a subsequent study will allow us to further explore the use of Pi/ PCr ratio as an outcome measure in HD clinical trials. Recruiting patients from the previous study will allow us to test the reproducibility of the initial findings in the same patient population and measure longitudinal changes. New patients at the early stage of the disease will also be recruited to validate our findings in an independent study population. In addition, we wish to include premanifest individuals to assess whether an abnormal brain energy profile can be identified before onset of overt HD symptoms, which is essential for development of future therapies.


 

1 Mochel F, Charles P, Seguin F, et al. Early energy deficit in Huntington disease: identification of a plasma biomarker traceable during disease progression. PLoS ONE. 2007 Jul 25; 2(7):e647. doi:10.1371/journal.pone.0000647.

2 Mochel F, Haller RG. Energy deficit in Huntington disease: why it matters. J Clin Invest. 2011 Feb 1;121(2):493–499. doi: 10.1172/JCI45691.

3 Mochel F, Duteil S, Marelli C, et al. Dietary anaplerotic therapy improves peripheral tissue energy metabolism in patients with Huntington’s disease. Eur J Hum Genet. 2010 Sep; 18(9):1057-60. doi: 10.1038/ejhg.2010.72. Epub 2010 May 26.

4 Weiner DH, Fink LI, Maris J, et al. Abnormal skeletal muscle bioenergetics during exercise in patients with heart failure: role of reduced muscle blood flow. Circulation. 1986 Jun; 73(6):1127-36.