Central Nervous System Watch

Pharmacy Times, March 2011 Central Nervous System, Volume 77, Issue 3

Maternal History a More Reliable Risk for Alzheimer’s Disease

Researchers from the University of Kansas School of Medicine designed a longitudinal brain imaging study that examined the effect of family history on the development of Alzheimer’s disease (AD). After age, family history is the second most significant risk factor for AD.

The study, published in Neurology on March 1, 2011, enrolled 11 individuals with a maternal history of AD, 10 with a paternal history of AD, and 32 with no parental history. These individuals were similar in age, gender, education, and mini-mental status examination score. They all received a magnetic resonance imaging at baseline and at 2-year follow-up. Patterns of regional gray matter atrophy, an indicator of AD later in life, were also examined. It was found that individuals with a family history had significantly increased whole-brain gray matter atrophy compared with individuals without a family history.

The researchers further analyzed the individuals with a family history and found that only maternal history was associated with brain change, and individuals with maternal history had significantly greater atrophy in certain brain regions. The authors hypothesize that this apparent maternal transmission of risk for AD may be due to defects in mitochondrial DNA, which is transmitted only by the mother, and may be responsible for alterations in glucose metabolism in AD brain tissue. Because the individuals were asked about family history, parents may not have had AD but another dementia, which would confound the results. Additionally, the small sample size may have limited the power of the study. Despite these limitations, the results are consistent with the findings of other studies that link maternal history to an increased risk for AD. PT

Spinal Fluid Proteins May Be Key to Diagnosing Chronic Fatigue Syndrome

Chronic fatigue syndrome (CFS) and neurologic post-treatment Lyme disease syndrome (nPTLS), 2 conditions with similar symptoms of fatigue and cognitive dysfunction, are difficult to differentially diagnose, and some have even argued they may share the same etiology. However, a new study published online on PLoS One in February 2011 found that using a proteomics approach, these 2 similar neurologic syndromes can be distinguished by analyzing protein components of cerebrospinal fluid (CSF) samples.

Researcher Steven Schutzer and colleagues from the University of Medicine and Dentistry of New Jersey in Newark collected CSF samples from CFS (n = 43) and nPTLS (n = 25) patients as well as healthy controls (n = 11). Performing high-resolution mass spectrometry and analyzing the pooled samples qualitatively and quantitatively, the researchers found that the CSF proteins that were identified could be distinguished from each other between all 3 groups. The researchers found significant differences in 3 aspects: the magnitude of the increase in complement protein, the type of protein identified, and the magnitude of the decrease in certain proteins known to affect CNS cellular architecture. All 3 of these differences, the scientists argue, demonstrate that the pathological mechanism that causes CFS is distinct from the mechanism that causes nPTLS.

The results were also significant because hundreds of different proteins were identified, which can serve as distinct biomarkers for CFS and nPTLS. Currently, there are no reliable biomarkers that can be used to diagnose a patient with CFS. Being able to identify any biomarker or surrogate biomarker is imperative to advance diagnostic and therapeutic interventions. Although more studies are required to further analyze these candidate biomarkers, the results provide an important breakthrough in the understanding of these 2 similar neurologic diseases.

Low EGF May Predict Parkinson's Dementia Later in Life

In another quest for a valuable biomarker, researchers from the University of Pennsylvania assessed plasma proteins of patients with Parkinson’s disease that had the potential to serve as biomarkers for cognitive impairment. Although 83% of patients with Parkinson’s disease develop cognitive impairment and even dementia during their disease course, neither the timing of onset nor the severity of cognitive symptoms can be accurately predicted.

The study, published online in the Annals of Neurology in March 2011, recruited 70 patients with Parkinson’s disease and evaluated their cognitive status with the Mattis Dementia Rating Scale-2 at baseline and on annual follow-up visits. Baseline levels of 102 plasma proteins were also determined by immunoassay. With linear regression, 11 proteins were identified as biomarkers of cognitive impairment, but the best candidate biomarker was epidermal growth factor (EGF; P <0.001). Not only did a low level of EGF correlate with poor cognitive function at baseline, it also predicted an 8-fold greater risk of cognitive decline to dementia at follow-up for those with intact baseline cognition.

The effect of low EGF levels in Parkinson’s disease dementia may be due to the neurotrophic effects EGF has on dopaminergic neurons. Due to the association of a low baseline EGF with dementia later in life, EGF signaling may be involved on a molecular level in the progression of cognitively normal patients to patients with dementia. “Such a predictive biomarker,” the authors conclude, “might prove quite useful in identifying atrisk populations for clinical intervention with trial therapeutic agents.”