Just as they are doing for Alzheimer's, researchers are trying to pinpoint the earliest clinical signs of Parkinson's disease (PD). Though physicians identify PD based on difficulties with movement, a host of non-motor symptoms may come first. To characterize these, the De Novo Parkinson (DeNoPa) study is following a cohort of recently diagnosed PD patients and healthy controls. In baseline results reported in the October 1 Neurology, scientists led by Brit Mollenhauer and Claudia Trenkwalder, Paracelsus-Elena Klinik, Kassel, Germany, claim that they can distinguish patients from controls with more than 90 percent accuracy just by assessing non-motor symptoms. "We can say who has PD without even looking at the motor symptoms," said Mollenhauer. The results have implications for diagnosis and future clinical trials, Mollenhauer told Alzforum.
"Studies of non-motor signs in de novo PD are sparse, and [these symptoms] are often poorly recognized and inadequately treated in PD," wrote Penelope Hallett, McLean Hospital, Belmont, Massachusetts, an affiliate of Harvard Medical School, to Alzforum in an email. "This study now provides a systematic and important assessment of non-motor signs in de novo PD patients," she wrote.
Physicians typically diagnose PD based on the presence of tremor, slowed movement, rigid muscles, or hunched gait typical or of the people with the disease, as well as whether the person responds to treatment with levodopa (see Hughes et al., 1993). However, people with PD are often plagued by disturbances in rapid eye movement (REM) sleep, constipation, and loss of their sense of smell. While scientists are aware of these signs, they have not worked them into PD diagnosis. Could a combination of these traits help spot the disease before motor symptoms creep up? The DeNoPa study systematically characterizes non-motor signs in patients who have just been diagnosed with Parkinson's, then observes whether these signs predict disease in healthy controls.
Starting in September of 2008, Mollenhauer and colleagues recruited 40- to 85-year-old newly diagnosed PD patients from the Paracelsus-Elena Klinik, the largest PD hospital in Germany. Healthy age-, sex-, and education-matched friends and relatives volunteered as controls. Altogether, 159 patients and 110 controls spent two to three days at the hospital completing a battery of tests, including health questionnaires, cognitive testing, smell tests, an echocardiogram, blood tests, a brain ultrasound, magnetic resonance imaging, and a sleep study called polysomnography (PSG), which monitors brain waves, blood oxygen level, heart rate, breathing, and movements during sleep. In addition to the data reported in this paper, Mollenhauer and colleagues are collecting fluid samples for separate analysis.
Overall, PD patients had more non-motor abnormalities than controls. They slept poorly and had gastrointestinal problems. Unexpectedly, a faster heartbeat in routine echocardiogram and lower serum cholesterol cropped up in the patient group, as well. People with PD also had more trouble distinguishing aromas, and a higher ultrasound signal from the substantia nigra, the site of dopaminergic neuron loss in PD. Though a common abnormality in PD patients, the cause of this remains unclear.
In addition, polysomnography identified a form of REM sleep behavior called REM behavioral events (RBE). RBE entails mild but purposeful motions or speech. Fifty-one percent of PD subjects and—surprisingly—15 percent of healthy controls, experienced RBE. Data about RBE in the general population are scarce. The researchers will follow this population of healthy controls, and recruit more who exhibit RBE, to see if it predicts PD.
Scientists previously identified REM behavior disorder (RBD), a more violent form of sleep disturbance, as a risk factor for Parkinson's (see ARF related news story and ARF related news story). In RBD, the patient may kick their bed partner, or fall out of bed altogether. Mollenhauer said she will elaborate on the sleep data from DeNoPa in an upcoming paper in the journal SLEEP.
Put together, all of these non-motor symptoms distinguished PD from controls with 96 percent accuracy, independently of motor dysfunction. This predictive ability dovetails with neuropathology. Postmortem data show that α-synuclein aggregates appear in many areas of the nervous system by the time degenerating dopaminergic neurons lead to PD symptoms, hinting that non-motor symptoms could appear first (see Del Tredici and Braak, 2012). "That suggests these non-motor signs could be used to diagnose Parkinson's disease even before motor symptoms arise," said Mollenhauer (see ARF related news story).
If a particular mixture of non-motor signs heralds PD, then scientists could use it to enrich clinical trial cohorts by picking out people who do not yet meet motor symptom criteria, Mollenhauer told Alzforum. Researchers could also use these non-motor signs as markers to measure the effectiveness of future therapies, she added. Once a disease-modifying therapy becomes available, earlier diagnosis will lead to speedier treatment, she said. While Mollenhauer believes the official clinical criteria need to be changed to include non-motor signs, she cautioned that her data should be independently validated first.
Mollenhauer sits on the executive steering committee for the larger, multi-center, international Parkinson's Progression Markers Initiative (PPMI ), which seeks biomarkers to measure PD progression. While the single-center DeNoPa study will test subjects less often—every two years rather than every three to six months in PPMI—it will do so for 10 to 15 years of follow-up versus five for PPMI. Moreover, PPMI does not measure sleep and brain ultrasound. Both studies continue to enroll people at risk for PD, such as those with spontaneous RBD, which was recently shown to precede motor symptoms by up to 29 years (see Schenck et al., 2013 ).—Gwyneth Dickey Zakaib
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- Hughes AJ, Daniel SE, Blankson S, Lees AJ. .
- Del Tredici K, Braak H. .
- Schenck CH, Boeve BF, Mahowald MW. .