Master’s Thesis, 30 ECTS
The Programme for Master of Science in Psychology, 300 ECTS Autumn 2019
Supervisor: Magdalena Domellöf & David Bäckström
An Alzheimer-type cerebrospinal fluid
profile in early
Parkinson’s disease
Author: Mario-Christofer Chamoun
I cannot express enough thanks to my supervisors Magdalena Domellöf and David Bäckström for their extraordinary support throughout this study. Thank you for giving me this opportunity and for believing in me!
Abstract
In recent years, several studies have discovered traces of Alzheimer's (AD) biomarkers in a large portion of patients with Parkinson's disease (PD), which have been associated with subsequent dementia (PDD). However, the manifestation of AD biomarkers in PD is not fully understood. At present, few studies have investigated how common AD biomarkers are in newly diagnosed and unmedicated patients with PD. This cross-sectional cohort study investigated whether AD biomarkers were present in unmedicated and newly diagnosed patients with PD and patients with PD and overlapping clinical symptoms (cognitive impairment, depression, olfactory dysfunction). Cerebrospinal fluid (CSF) levels of AD biomarkers Amyloid-β-42 (Aβ42), phosphorylated-tau (p-tau), and total-tau (t-tau) were assessed in 343 patients with the mean age of 68,69 (SD=9,60), including 31 healthy controls with the mean age of 68,90 (SD=5,64). The participants were recruited from The New Parkinson Patient in Umea (NYPUM & PARKNY). The results showed a significant difference in CSF AD biomarkers between patients with PD and healthy controls, but not in patients with PD and overlapping clinical symptoms. The results point to the presence of AD pathology in early PD; however, the presence of AD pathology could not be further strengthened by the clinical overlapping symptoms. More prospective studies on newly diagnosed patients with PD need to be carried out to investigate the prognostic values of the presence of AD pathology found in PD.
Keywords: Alzheimer’s disease, Parkinson’s disease dementia, Parkinson’s disease, pathology, biomarkers, cognitive impairment, depression, olfactory dysfunction, dopaminergic treatment, cognitive tests, cognitive domains.
Abstrakt
Under de senaste åren har spår av Alzheimers (AD) biomarkörer upptäckts hos en stor andel patienter med Parkinson sjukdom (PD), som har associerats med utveckling av demens (PDD). Emellertid är manifestationen av AD biomarkörer i PD inte fullt ut förstådd. För närvarande är det få studier som har undersökt AD biomarkörer hos patienter med nydebuterad PD, innan påbörjad medicinering. Denna kliniskt baserade tvärsnittsstudie undersökte om AD biomarkörer förekom hos patienter med nydebuterad PD och hos patienter med PD och kliniskt överlappande symptom (kognitiv svikt, depression och nedsatt luktsinne), innan påbörjad medicinering. Cerebrospinal vätska (CSF) av AD biomarkörerna Aβ42, p-tau, and t-tau analyserades i 343 patienter i åldern M= 68,69 (SD=9,60) tillsammans med 31 friska kontroller i åldern M= 68,90 (SD=5,64). Alla deltagare rekryterades från databaserna Ny Parkinson Patient i Umeå (NYPUM & PARKNY). Resultatet visade på signifikanta skillnader av AD biomarkörer i patienter med PD jämfört med friska kontroller, men inte i patienter med kliniskt överlappande symptom. Resultaten pekar mot förekomsten av AD patologin i ett tidigt sjukdomsskede i PD. Emellertid kunde förekomsten av AD patologin inte styrkas med de kliniskt överlappande symptomen.
Nyckelord: Alzheimers sjukdom, Parkinson sjukdom. Parkinson sjukdom demens, patologi, biomarkörer, kognitiv svikt, depression, nedsatt luktsinne, dopamin behandling, kognitiva tester, kognitiva domäner.
An Alzheimer-type cerebrospinal fluid profile in early Parkinson’s disease
Parkinson's disease (PD) is a movement disorder that affects populations worldwide as well as one of the most common neurodegenerative disorders (Pringsheim, Jette, Frolkis, &
Steeves, 2014). PD also affects the quality of life and presents a burden on caregivers as the disease advances (Rajiah, Maharajan, Yeen, & Lew, 2017). The prevalence is estimated to be to one percent among people over 60, which also increases with age (Wong, Gilmour, &
RamageMorin, 2014; de Rijk et al., 2000). Schapira (2013) suggests that the life-time prevalence is four percent and is expected to double in 2030.
PD gives rise to a collection of clinical symptoms, including bradykinesia, hypokinesia, rigidity, tremor, postural instability, poor coordination, and gait impairment. These symptoms are referred to as motor symptoms (Lotankar, Prabhavalkar, & Bhatt, 2017). Apart from motor symptoms, there are also non-motor symptoms such as olfactory dysfunction, cognitive impairment, depression, hallucinations, dementia, fatigue, sleep disorders, and autonomic dysfunction (Williams-Gray & Worth, 2016).
The degeneration of dopaminergic cells in the substantial nigra (pars compacta) is a vital part of basal ganglia dysfunction in PD (Janvin, Aarsland, & Larsen, 2005). The dysfunction is found in movement disorders, cognitive deficits, and psychiatric disorders (Alexander, DeLong, & Strick, 1986).
The misfolded α-synuclein (α-syn) protein is one of the pathological hallmarks of PD, which leads to aggregates in the cell body that prompts the development of Lewy body and Lewy neurites (Coughlin, Hurtig, & Irwin, 2019). Braak, Ghebremedhin, Rüb, Bratzke, & Del Tredici (2004) describe the pathological progress of α-syn in six stages. The distribution of the α-syn protein reaches medulla oblongata (beneath pons), the dorsal motor nucleus of the vagus, and the olfactory bulb during the preclinical stages 1-2. During stage 2, the α-syn aggregations reach locus coeruleus and raphe nuclei, progresses through the pons upward and enters the midbrain and basal forebrain, where it proceeds to the substantia nigra (stage 3-4). During the final stages 5-6, the α-syn aggregations ultimately reach the neocortex (Braak, Ghebremedhin, Rüb, Bratzke, & Del Tredici, 2004).
Overlapping clinical symptoms
Mild cognitive impairment is an overlapping clinical symptom that is common in neurodegenerative diseases (Petersen, 2004). Mild cognitive impairment in PD (PD-MCI), however, is based on cognitive and clinical criteria (Litvan et al., 2011). Studies of newly diagnosed patients with PD-MCI show the prevalence to range from 19% to 34% (Aarsland et al., 2009; Muslimovic, Post, Speelman, & Schmand, 2005; Pedersen, Larsen, Tysnes, & Alves, 2013; Pfeiffer, Løkkegaard, Zoetmulder, Friberg, & Werdelin, 2014). Furthermore, studies suggest that patients with PD-MCI have later disease onset, older age, and higher motor disability compared to patients with PD and intact cognitive function (Janvin, Aarsland, Larsen,
& Hugdahl, 2003; Williams-Gray, Foltynie, Brayne, Robbins, & Barker, 2007). Other studies have shown an increased risk of dementia (PDD) and higher mortality rate among patients with PD-MCI (Domellöf, Ekman, Forsgren, & Elgh, 2015; Janvin, Larsen, Aarsland, & Hugdahl, 2006; Bäckström, 2019). The studies also showed increased caregiver distress and adverse effects on the quality of life (Jones et al., 2017).
The most frequently mentioned cognitive dysfunctions in PD are memory-, executive- , and visuospatial dysfunction (Alves et al. 2010; Irwin, Virginia & Trojanowski, 2013).
Working memory- and executive dysfunction are associated with the frontostriatal circuit of the basal ganglia, and 50% of these patients have comparable cognitive dysfunctions as patients with frontal lobe damage (Kehagia, Barker, & Robbins, 2013; Tekin & Cummings, 2002).
Additionally, overall cognitive performance is impaired in patients with PD in contrast to healthy controls (Aarsland et al., 2009). Cognitive deficits can be defined through a spectrum that begins with PD-MCI in early disease stages, which develops to dementia (PDD) as the disease progresses (Litvan et al., 2012; Dirnberger & Jahanshahi, 2013). Several studies investigate the performance on cognitive tests related to the future development of PD-MCI and PDD. Mahieux et al. (1998) found that the Stroop Task, verbal fluency task, and picture completion test to predict subsequent PDD. These cognitive tests are sensitive to specific cognitive abilities (i.e., planning, attention, inhibition) that are generally impaired in PD (Lewis, Slabosz, Robbins, Barker, & Owen, 2005). Furthermore, dopamine replacement treatment Levodopa (L-dopa) is the most commonly used drug to alleviate motor symptoms in PD ("Levodopa," 2012). L-dopa is also known to interfere with cognitive performance, which has led to the awareness of dopaminergic involvement in cognitive functioning (Lange et al., 1992).
Depression is an overlapping clinical symptom common in neurodegenerative diseases, especially within basal ganglia dysfunction, and within PD, the estimations of the mood disorder are inconsistent (Levenson, Sturm, & Haase, 2014; Mayberg, 1994). In varied incidence of PD, 30-40% of patients experience depression, and in newly diagnosed patients with PD, 16% to 50% of patients experience depression (Kessler et al. 2003; Aarsland et al., 2009; Schulz & Arora, 2015; Enache, Winblad & Aarsland, 2011: Giladi et al., 2000; Zhu, van Hilten, & Marinus, 2016; Ravina et al., 2007; Ravina et al., 2009). The risk factors that are associated with the development of depression are high L-dopa dosage and daytime sleepiness (Zhu, van Hilten, & Marinus, 2016; Ravina et al., 2007; Ravina et al., 2009). Furthermore, patients with PD and depression are associated with increased risk of future PD-MCI and PDD compared to non-depressed patients with PD (Kessler et al. 2003; Aarsland et al., 2009; Schulz
& Arora, 2015; Enache, Winblad & Aarsland, 2011: Giladi et al., 2000). Postuma et al. (2012) suggest that patients with PD and depression are associated with multiple neurotransmitter dysfunctions, that are linked to α-syn aggregates in the early disease stage that may also be present before motor symptoms develop (Jacob, Gatto, Thompson, Bordelon, & Ritz, 2010;
Ravina et al., 2009). In addition, other studies have shown that decreased metabolism in the caudate nucleus, and frontal cortex are related to depressive symptoms in PD (Tekin &
Cummings, 2002; Mayberg, 1994). Aside from the early presence of depressive symptoms, mood disorder has been measured to have a negative impact on health-related quality of life in PD (Schrag, 2000; Weintraub, Moberg, Duda, Katz, & Stern, 2004).
Olfactory dysfunction (OD) is common among neurodegenerative diseases, and in PD, 50% to 90% of patients exhibit OD at the time of diagnosis, which may also be present before clinical symptoms appear (Doty, 2017; Fullard, Morley & Duda, 2017). Domellöf, Lundin, Edström, & Forsgren (2017) found that 73% of patients exhibited OD at the time of PD diagnosis. Among these studies, it was also shown that patients with PD and OD are associated with cognitive deficits and PDD (Domellöf, Lundin, Edström, & Forsgren, 2017; Gjerde et al., 2018). Olfactory dysfunction is also involved in the olfaction bulb, where the misfolded α-syn proteins initiate aggregation (Doty, 2012; Braak, Ghebremedhin, Rüb, Bratzke, & Del Tredici, 2004). Beach et al. (2009) demonstrated that concentrations of α-syn proteins in the olfactory bulb measure the severity of α-syn pathology in the brain. Additionally, the Mini-Mental State Examination (MMSE) was found to be associated with the concentration of α-syn proteins (Beach et al., 2009). Other studies have investigated the patients' perspectives of the disease.
Those with olfactory dysfunction at an early stage in PD described the loss of smell and taste as highly "troublesome" (Politis et al., 2010).
Overlapping Pathology
Aside from early PD, the overlapping clinical symptoms such as cognitive deficits, depression, and olfactory dysfunction are common in dementia syndromes. Once cognitive impairment affects the day-to-day functions of a patient, it is considered a dementia syndrome, which is found in up to 80% of survivors (Gale, Acar, & Daffner, 2018; Hely, Reid, Adena, Halliday, & Morris, 2008; Aarsland, Andersen, Larsen, & Lolk, 2003; Williams-Gray et al., 2009). Recently, Alzheimer's disease (AD) pathology has been considered being present in PD (Galvin & James, 2006; Stav et al., 2015). AD pathology interfering with α-syn pathology is associated with developing PD-MCI and PDD (Stav et al., 2015).
Amyloid-β-42 (Aβ42), phosphorylated-tau (p-tau), and total-tau (t-tau) are biomarkers in cerebrospinal fluid (CSF) that are the hallmarks of AD pathology, where CSF provides a window to study the biomarkers in the brain (Sperling et al., 2011; Alves et al., 2010;
Bäckström et al., 2019). The first biomarker, which is the misfolded Aβ42 aggregation, found extracellularly, prompts plaque formation in the cells. The aggregation begins the plaque formation in the orbitofrontal neocortex, which progresses around the neocortex, and enters the hippocampus, basal ganglia, and amygdala. The aggregation ultimately reaches the cerebellar cortex and lower brain steam (Goedert, 2015). According to studies, lower levels of assessed CSF Aβ42 are associated with plaque formation in the brain (Rambaran & Serpell, 2008; Stav et al., 2015).
Abnormal developed tau proteins contain inclusions of neurofibrillary tangles that extend from cell to cell, which contributes to cell death. The inclusion of neurofibrillary tangles begins in the locus coeruleus, entorhinal, and trans entorhinal (higher parts of the pons), which proceeds around the neocortex and hippocampus (Goedert, 2015). According to studies, higher levels of CSF p-tau and t-tau are associated with neurofibrillary tangles in the brain (Pîrşcoveanu et al., 2017; Rosenmann, Blum, Kayed, & Ittner, 2012).
50% of patients with PDD develop plaque formation and inclusions of neurofibrillary tangles to the same extent as patients with AD (Irwin, Lee & Trojanowski, 2013). Bejanin et al., (2017) suggest that neurofibrillary tangles may be causing cognitive deficits in AD, while in PD, Aβ42 is associated with memory impairment and PD-MCI (Siderowf et al., 2010; Alves et al., 2010; Terrelonge, Marder, Weintraub, & Alcalay, 2016). A study by Compta et al. (2009) showed that deficits in cognitive abilities such as recall, recognition, and naming were associated with CSF tau proteins in PD, while in PDD, deficits in recognition and naming were associated with CSF tau proteins.
In the Norwegian ParkWest study, Alves et al. (2010) found a reduction of CSF Aβ42 in 109 unmedicated and newly diagnosed patients with PD compared to 36 healthy controls, although the tau proteins were not significantly altered in early PD (Alves et al., 2010). Parnetti et al. (2008) suggest that the alternations of tau proteins may be significant in the later stages of PD. However, it is unclear how early the alternation of tau proteins can be detected in PD.
Other studies have found older age at baseline, together with cortical plaque formation to be associated with the rapid progression of dementia (Compta et al., 2011). Winer et al. (2018) found that Aβ42 and tau proteins were not significantly altered when comparing PD-MCI patients with PD and healthy controls.
Rapp et al. (2008) investigated patients with AD and depression in a large cohort study based on the National Alzheimer's Coordinating Center, comparing 5,873 non-depressed patients with AD to 595 depressed patients with AD. The study showed that depressed AD group had higher levels of neurofibrillary tangles (Rapp et al., 2008). Based on another study by Rapp et al. (2006), patients with AD and depression are associated with hippocampal changes and rapid cognitive decline. This study also suggested that patients with AD and
depression may have a different pathology compared to non-depressed patients with AD (Rapp et al., 2006).
To our knowledge, studies of CSF AD biomarkers in patients with PD and overlapping clinical symptoms (excluding PD-MCI) have not yet been performed. However, a few studies have investigated CSF AD biomarkers in newly diagnosed and unmedicated patients with PD, where findings are inconsistent. The majority of studies have explored the field in cross- sectional study design with a small sample size and varied incidence of PD, resulting in mixed outcomes. A well-defined large study cohort is needed to define the role of CSF AD biomarkers in patients with PD (Alves et al. 2010).
The importance of studying the overlap of CSF AD biomarkers in PD is to understand the relationship between both pathologies and their overlapping clinical symptoms in an early stage of the disease. Accordingly, the contribution of this study may generate confirmation to the few previous studies and provide new evidence of the overlapping, pathological interplay.
Aim and research questions
The objectives of this thesis are to investigate how common AD biomarkers is in newly diagnosed patients with PD and if AD biomarkers are associated with cognitive decline, olfactory dysfunction and depression.
1. How common is an Alzheimer-type CSF profile of AD biomarkers at the time of PD- diagnosis?
2. Is AD biomarkers associated with cognitive decline at the time of PD-diagnosis?
3. Is AD biomarkers associated with depression at the time of PD-diagnosis?
4. Is AD biomarkers associated with olfactory dysfunction at the time of PD-diagnosis?
Method Participants
The present study is cross-sectional and clinical-based with newly diagnosed and unmedicated patients with PD, that are recruited from two sets of databases. The inclusion criterions for participation in the study are completed CSF uptake and having fulfilled the Movement Disorder Society Clinical diagnostic criteria for PD with no initiated dopaminergic medication (Gibb & Lees, 1989).
The new Parkinson patient in Umea (NYPUM). The NYPUM database is a prospective population-based cohort study of incidence cases with Parkinsonism, PD, and idiopathic Parkinson's disease. Patients living in Umea with suspect Parkinson symptoms were referred from healthcare institutions to the Department of Neurology at the University Hospital of Umea. Any PD diagnosis required an agreement between the neurologists within the department, along with the fulfilment of the MDS criteria for PD (Gibb & Lees, 1989). The included patients were investigated and followed for at least five years, where 143 patients were diagnosed with PD during the inclusion period between January 1st, 2004, and May 1st, 2009. Out of the 143 patients included in this study, 98 patients with the mean age of 69,86 (SD=9,23) provided CSF and fulfilled the MDS criteria for PD. 19 females, and 26 males (n=45) were excluded from this cohort due to not completing CSF uptake or not fulfilling MDS criterion for PD. The excluded patients were older (M=73.99, SD=10,84) and had higher education years (M=10,61, SD=4,27). Additionally, the excluded patients had a higher disease severity (M=29,10, SD=14,78) and MADRS scores (M=5,81, SD=3,84) compared to other patients.
The new Parkinson patient in Umea (PARKNY). The PARKNY database is a continuation of the NYPUM-project. Since May 1st, 2009, after the NYPUM project ended, there were 150 additional cases of PD that had been discovered. The PARKNY database is a prospective population-based cohort of newly diagnosed patients with PD. The project was funded to establish an additional study population in order to validate previous findings from the NYPUM project and to strengthen the power of the collected data by combining the two databases. Approximately 203 patients were diagnosed with PD during the inclusion period between May 1st, 2009, and November 1st, 2018. The PARKNY study used a similar procedure as the NYPUM-project, although PARKNY used the revised version of MDS for PD-MCI. Out of the 294 patients, 245 were included. The excluded patients had not completed CSF uptake nor fulfilled the criterions for PD, where 12 females and 21 males (n=33) did not complete CSF uptake and had an overall poor data coverage. 4 females and 10 males (n=14) with the mean age of 69,81 (SD=10,21) did not fulfil the MDS criterion for PD. Additionally, the excluded patients had higher disease duration (M=17,3, SD=12,52) and education years (M=12,56, SD=4,71) with a longer disease duration (M=16,07, SD=10,76).
Healthy controls. AD biomarkers were obtained from 31 healthy controls that were age- and gender-matched. The healthy controls had the mean age 68,90 (SD= 5,64) and were based on the 50 first included in the NYPUM project. The inclusion criteria for healthy controls are no signs of dementia-, cognitive- or psychiatric disorders, and no neurodegenerative diseases along with a completed cerebrospinal fluid uptake. One male was excluded due to not completing CSF uptake. Additionally, the excluded male had comparable scores.
The Regional Medical Ethics Board has confirmed both projects (NYPUM &
PARKNY) in Umea, where all patients have written consent.
Cerebrospinal fluid assessment
Cerebrospinal fluid. CSF was collected from newly diagnosed PD patients before initiating L-dopa treatment. When performing a lumbar puncture, a needle is pierced into the lumbar spinal canal to absorb CSF from the patients (Doherty & Forbes, 2014). Sandwich enzyme-linked immunosorbent assay (ELISA) was used to detect and capture antibodies, and by inducting antigen, the activation of the immune system attracts the antibodies (Crowther, 1995). To analyse levels of Aβ42 and tau proteins, sandwich ELISA (INNOTESThTAU-Ag;
Innogenetics), that is specialized in capturing tau proteins, and sandwich ELISA (INNOTEST β-AMYLOID (1-42); innogenetics) were both used. The lowest acceptable sample concentration for these analyses was 50 Nanogram/Liter [ng/L], which indicates that 50 ng/L is the lowest concentration to reliably analyse with the sandwich ELISA (Bäckström et al., 2015; Armbruster & Pry, 2008).
Clinical assessments
Disease severity. UPDRS is a traditional rating scale based on the recommendations from the Movement Disorder Society, with the purpose of rating four dimensions of symptoms in PD. The rating scale comprehends the following set of symptoms: non-motor experience (UPDRS I), motor experience (UPDRS II), motor examination (UPDRS III), and motor complexity (UPDRS IV). Combining the four dimensions provided a result of disease severity at baseline while patients were unmedicated (Fahn & Elton, 1987), and in this study, only UPDRS III at baseline is used. Any higher UPDRS III scores indicate a more significant motor severity. The UPDRS III examines speech, facial expression, rigidity of the neck and four extremities, finger taps, hand movements, pronation/supination, toe-tapping, leg agility, arising
from chair, gait, freezing of gait, postural stability, posture, global spontaneity of movement and postural tremor (Goetz et al., 2007).
The Hoehn and Yahr scale was administrated in addition to UPDRS, which provided a progression of motor symptoms through a hierarchical staging system. The stages were: Stage 1–unilateral (one-sided) motor-symptoms, stage 1.5 -unilateral and axial motor symptoms, stage 2–moderate bilateral (two-sided) motor symptoms, stage 2.5–mild bilateral motor symptoms and recovery in pull test, stage 3–bilateral motor-symptoms and moderate posture imbalance, stage 4–bilateral motor symptoms and severe posture imbalance, stage 5– physical incapacity (Goetz et al., 2004; Hoehn & Yahr, 1967). Both instruments were applied by an experienced neurologist on the unmedicated patients at the time of diagnosis.
Mood disorder. Depression was measured with the Montgomery Åsberg Depression Rating Scale (MADRS), where patients with a score over 8 were identified as depressed. Scores ranging from lowest 0 score to highest 34 score (Montgomery & Åsberg, 1979). Cronbach’s α measures the internal consistency which was at the level of 0,93 (good) (Paiva-Medeiros et al., 2015) A total of 23 females and 40 males (n=63) with the mean age 67,91 (SD=9,71) were excluded due to missing MADRS scores. The excluded patients had higher MMSE scores (M=28,17, SD=2,15), higher education years (M=11,19, SD=3,40), higher in all CSF markers Aβ42 (M=634, SD=29,38), p-tau (M=43,32, SD=23,32) and t-tau (M=295, SD=208) compared to included patients.
Olfactory function. The Brief Smell Identification Test (BSIT), which consists of 12 items of odor, was applied in order to examine the olfactory function. Each item within the test contains forced choice with four alternatives, where forced-choice commits the patients to provide an answer regardless of not having an opinion. The correct identification yielded one point, where patients with a score under 8 were identified as having mild olfactory dysfunction, while those that scored under 4 were seen as having severe olfactory dysfunction (Haytoğlu, Dengiz, Muluk, Kuran, & Arikan, 2017; Doty, Marcus, & William Lee, 1996). Cronbach’s α was at the level of 0,68 which shows an acceptable level of internal consistency (Wilson et al., 2011)There were 92 excluded patients because no B-SIT was provided, and these were 29 females and 63 males with the mean age 69 (SD=8,67). In addition, the excluded patients had comparable measurements: MMSE scores (M=27,93, SD=2,27) and MADRS scores (M=5,0, SD=4,80).
Cognitive evaluation. Mini-Mental State Examination (MMSE) was assessed as a brief evaluation of cognitive performance, with 20 questions and five to ten-minute administration. Ranging from lowest 0 score to highest 30 score. (Folstein, Folstein & Mchugh, 1975). Cronbach’s α was at the level of 0,78 which shows an good level of internal consistency (Oľga, Silvia & Jana, 2016)
Mild cognitive impairment (PD-MCI). Criteria from the Movement Disorder Society Task Force (MDS) for PD-MCI were integrated with PARKNY and NYPUM. MSD recommends two neuropsychological tests for each cognitive domain (language, executive function, working memory, attention, and visuospatial function). Performances under 1SD to 2SD compared to demographically-matched norms were defined as impairments. The cognitive impairment is present in at least two tests in a single cognitive domain, or one test in at least two cognitive domains. The MDS recommends that the change in cognitive abilities is reported by either the patient or an informant (Litvan et al., 2012). The 83 excluded patients that were 33 females and 50 males with the mean age 70,42 (SD=9,93) did not provide neuropsychological testing. In addition, the excluded patients had comparable education years (M=10,10, SD=3,46), lower CSF Aβ42 (M=604, SD=192), higher p-tau (M=42,25, SD=16,44) and higher t-tau (M=291, SD=148) compared to other patients.
Process. The patients from the PARKNY project were diagnosed with PD-MCI by professional neuropsychologists and re-evaluated by the author of this research, where MDS
recommendations were applied. The participant's premorbid level was considered when evaluating the cognitive-profile, which is in line with the method used by the neuropsychologist.
Procedure
The clinical examinations were localized at the department of neurology in the University Hospital of Umeå (NUS) in Norrland, Sweden. The request for participating in the PARKNY study was managed through patient revisits for regular PD inspections at NUS, where the requirement for participating included additional visits within 1-2 weeks after approval. The following clinical examinations were carried out on the patients: MADRS and B-SIT, UPDRS, H&Y, lumbar puncture, neuropsychological assessment — the total estimated time was 3-4 hours per visit. The clinical examinations were annually repeated, where neurologists specialized in movement disorder conducted lumbar puncture to obtain CSF samples while UPDRS and H&Y were applied for the measurement of disease severity. In the NYPUM database, the baseline visit for PD diagnoses was recorded by the baseline doctor and, in second hand, examined by a chief physician. The neuropsychological assessment, with standardized questionnaires and tests, was administrated by professional neuropsychologists.
Collection of data. Data were collected through patient medical records at NUS. The collection of MADRS, B-SIT, and psychological assessment were limited to 6 months after study entry before initiating L-dopa treatment. However, only a few patients had initiated L- dopa treatment, and UPDRS III and H&Y were collected merely at baseline.
Statistics
Statistical Package for Social Science (SPSS) version 24 was used for statistical analysis. Differences between clinical groups were investigated with the Independent-sample t-test, Chi-square test, or Mann Witney u test as appropriate.
Skewness. Skewness, in the interval of -2 to +2, was regarded as "symmetrical skewed”
data (George & Mallery, 2010).
Statistical settings. p ≤ 0,05 was interpreted as statistical significant. A filter was set to exclude patients not fulfilling P diagnosis and patients not completing CSF uptake. Variables (e.g., p-tau, t-tau) with "highly skewed" or "moderate skewed" distribution were logarithmically transformed when included in a parametric test.
Comparing groups. The independent-sample t-test measured the mean between two groups, and Levene's test measures the variance distribution. In the independent t-test, the grouping variables (depression, MCI, olfactory) were set as "grouping variable" and variables such as UPDRS III, education years, e.g., Was set as "test variable" comparing nominal variables (e.g., gender) with the MCI and depression groups, a Chi-square test was applied to evaluate the difference in units and frequency distribution.
A non-parametric test Man Whitney u test was used when comparing "highly skewed"
and "moderate skewed" variables between groups such as P-tau and T-tau.
Correlation. Spearman's correlation assessed the monotonic correlation coefficient between clinical tests and AD biomarkers. The significance level of spearman's rho provides the direction and strength of numeric variables (e.g., MMSE, MADRS). In the "variable"
column, the clinical tests and Aβ42, p-tau, and t-tau were set, before conducting the analysis.
Ethical considerations
Information regarding consent and participation was verbally described by attending researchers, including doctors and nurses. Approving research participation indicates that the
patient is aware of 1) the use of the obtained CSF- sample for scientific reasons; 2) there are additional visits for obtaining CSF and clinical data for scientific reasons; 3) giving access to clinical data (motor and non-motor) collected from visits during diagnosis and onward.
Participant's clinical and private information, including names and personal ID's, is protected in medical records and anonymized. All processed data is encoded and stored in a protected USB stick. Consequently, the data is applied in line with Parkny's and Nypum's approved ethical review.
Results
A Chi2 test assessed the difference in olfactory dysfunction and depression in patients with PD and healthy controls. The patients with PD were more likely to have olfactory dysfunction χ2(2, N=282) = 32,17, <.001 and depression χ2(1, N = 311) = 8,29, p= 0.004 when compared to the heaty controls.
An independent-sample t-test showed higher MMSE scores for the healthy controls compared to patients with PD t (63,11) = - 5,13, p <.001. Levene’s test showed uneven variance (F=12,78, p<.001). Degrees of freedom modified from 331 to 63,11. Patients with PD showed lower Aβ42-levels compared to healthy controls, t (371) = -3,95, p <.001. Further characteristics are presented in table 1.
Table 1
Descriptive and CSF profiles of patients with PD and healthy controls.
Descriptive N PD Healthy controls P-value Gender f/m
Age Education years
373 373 340
132/211 68,60 (9,60) 10,70 (3,67)
14/16 68,90 (5,64) 11,55 (3,59)
0,377 0,858 0,225 Intact olfactory function
Olfactory dysfunction Non-depression
Depression MMSE score
280 310 333
69 (27%) 184 (72%) 217 (77%) 64 (23%) 28,19 (2,0)
23 (79%) 6 (21%) 29 (100%)
0 (0%) 29,1 (0,82)
<.001a 0.004a
<.001b CSF biomarkers
N 343 30 -
Aβ42 ng/L 20% ↓ 664(219) 826 (231) <.001b
P-tau ng/L 38 [31-52] 43 [35-58] 0,069
T-tau ng/L 252 [181-344] 258 [215-348] 0,390
Note: bolded text indicates p<0,05. Values are set as mean (M) and standard deviation (SD).
Median [Mdn] and interquartile range [IQR] for nonparametric tests, except for gender.
ng/L= Nanogram/Liter, UPDRS III= Unified Parkinson’s Disease Rating Scale–motor examination, MMSE= Mini Mental State Examination, H&Y=Hoenh and Yahr scale. ↓= lower
aChi2 test p≤0,05
bIndipendent-sample t-test p≤0,05
cMann Whitney u test p≤0,05
Figure 1. The distribution of Aβ42 in healthy controls and patients with Parkinson’s disease (PD). The circles display the outliers.
PD-MCI versus PD
There was no significant difference in CSF AD biomarkers between patients with PD- MCI compared to patients with PD. Patients with PD-MCI were older compared to patients with PD t (165) = 3,00, p = 0,003. Lavene’s test showed uneven variance when comparing age at baseline (F=5,17, p=0,024); degrees of freedom were adjusted from 163 to 162. Patients with PD-MCI had higher motor disability compared to patients with PD t (44) = 2,38, p=0,19.
Lavene’s test showed unequal variance when comparing H&Y F (4,34, p=0,39). Degrees of freedom were adjusted from 142 to 124. Males were more likely than females to experience PD-MCI χ2 (1, N=165) = 8,19 p=0,004. Further characteristics are presented in table 2.
Table 2
Descriptive and CSF profiles of patients with PD-MCI and PD.
Descriptive n PD-MCI PD P-value
Gender F/M 165 15/50 45/55 0,004a
Age at baseline, years 165 69,32 (7,48) 65,08(10,8) 0,003b Education years 158 10,51 (3,42) 11,55 (3,42) 0,056 Disease duration 143 17,3 (13,6) 20,2 (21,7) 0,229 UPDRS III 136 21,89 (8,75) 20,24(8,80) 0,271 H&Y score 144 1,76 (0,53) 1,55 (0,56) 0,019a CSF biomarkers
N 65 100
Aβ42 ng/L 648 (216) 652 (228) 0,901
p-tau ng/L 38 [32 -51] 38 [30-49] 0,526 t-tau ng/L 272 [212-359] 227 [170-331] 0,057
Note: bolded text indicates p<0,05. Values are set as mean (M) and standard deviation (SD).
Median [Mdn] and interquartile range [IQR] for nonparametric tests, except for gender.
ng/L=nanogram/Liter, UPDRS III= Unified Parkinson’s Disease Rating Scale–motor examination, MMSE= Mini Mental State Examination, H&Y=Hoenh and Yahr scale.
aChi2 test p≤0,05
bIndipendent-sample t-test p≤0,05
cMann Whitney u test p≤0,05
Clinical tests correlation with AD biomarkers
The correlation between clinical test scores and AD biomarkers is displayed in table 3.
T-tau had a negative monotonic correlation with MMSE scores (see figure 2). Also, p-tau showed a negative monotonic correlation with MMSE scores (see figure 3).
Table 3
Correlation analysis of clinical tests in relation to AD biomarkers in patients with PD.
Cognitive tests Test scores mean (SD) CSF biomarkers Spearman’s rho (P-value) MMSE
(n=304)
28,15 (2,06) Aβ42
p-tau t-tau
0,098 -0,168*
-0,243**
MADRS (n=281)
4,79 (4,10) Aβ42
p-tau t-tau
-0,025 -0,071 -0,024 B-SIT
(n=253)
6,65 (2,54) Aβ42
p-tau t-tau
0,000 -0,009 -0,0370
≤0,05*; >.001**, MMSE=Mini Mental State Examination MADRS= Montgomery Åsberg Depression Scale, B-SIT= Brief Smell identification test, CSF=cerebrospinal fluid.
Figure 2. Scatter plots of MMSE scores and p-tau in Parkinson’s disease. Lower scores represents higher levels of p-tau
Figure 3. Scatter plots of MMSE scores and t-tau in Parkinson’s disease. Lower scores represents higher levels of p-tau.
Depression versus non-depressed
Out of the patients that provided MADRS, 39% of patients were depressed, and 61%
were non-depressed. An independent-sample t-test demonstrated that the depressed group was significantly older compared to the non-depressed group t (280) = 2,54, p=0,012. Further characteristics are presented in table 4.
Table 4
Demographics and cerebrospinal fluid profiles in patients with PD depression and patients with PD.
Descriptive n PD depression PD P-value
Gender F/M 281 20/43 90/128 0,148
Age at baseline, years 281 71,61 (0,56) 68,12 (9,68) 0,012b Disease duration 169 17,94 (16,66) 18,01 (14,43) 0,506
Education years MMSE
259 254
9,84 (3,47) 27,68 (2,07)
10,74 (3,80) 28,31 (1,95)
0,191 0,036 UPDRS III
H&Y
245 250
25,96 (9,40) 1,96 (0,65)
23,03 (9,94) 1,86 (0,63)
0,060 0,340 CSF biomarkers
n 64 217
Aβ42 ng/L 674 (217) 662 (219) 0,719
P-tau ng/L 38 [32-53] 38 [30-49] 0,710 T-tau ng/L 250[185-358] 252[183-340] 0,664
Note: bolded text indicates p<0,05. Values are set as mean (M) standard deviation (SD).
Median [Mdn] and interquartile range [IQR] for nonparametric tests, except for gender.ng/L
= Nanogram/Liter UPDRS III= Unified Parkinson’s Disease Rating Scale–motor examination, MMSE= Mini Mental State Examination, H&Y=Hoenh and Yahr scale.
aChi2 test p≤0,05
bIndipendent-sample t-test p≤0,05
cMann Whitney u test p≤0,05
Olfactory dysfunction versus intact olfactory
The independent t-test and Mann Whitney u test did not show a significant difference in CSF AD biomarkers between patients with PD and olfactory dysfunction and patients with PD and intact olfactory function. Out of the 253 that provided B-SIT, 73% of patients experienced olfactory dysfunction, and 27% had an intact olfactory function (See table 5).
Table 5
Demographics and CSF profiles in patients with olfactory dysfunction and patients with PD without olfactory dysfunction.
Descriptive n PD
olfactory dysfunction
PD
Intact olfactory function
P-value
Gender F/M 253 80/104 24/45 0,211
Age at baseline, years 251 68,50 (9,64) 68,44 (10,53) 0,962 Disease duration 148 17,87 (23,16) 17,44 (13,78) 0,911
Education years MMSE
230 232
10,60 (3,73) 28,18 (1,78)
10,41 (3,98) 28,25 (1,84)
0,749 0,289 UPDRS III
H&Y MADRS
222 224 217
23,93 (9,92) 1,91 (0,66) 5,26 (5,52)
22,68 (9,39) 1,91 (0,66) 4,41 (4,47)
0,402 0,941 0,289 CSF biomarkers
n 67 184
Aβ42 ng/L 671 (225) 647 (220) 0,460
P-tau ng/L 39 [32-53] 36 [29-57] 0,480
T-tau ng/L 259[187-341] 237[154-346] 0,476
Note: bolded text indicates p<0,05. Values are set as mean (M) standard deviation (SD).
Median [Mdn] and interquartile range [IQR] for nonparametric tests, except for gender. ng/L
=Nanogram/Liter UPDRS III= Unified Parkinson’s Disease Rating Scale–motor examination, MMSE= Mini Mental State Examination, H&Y=Hoenh and Yahr scale.
aChi2 test p≤0,05
bIndipendent-sample t-test p≤0,05
cMann Whitney u test p≤0,05
Discussion
This study investigated the presence of CSF AD biomarkers in a clinical-based, cross- sectional cohort of unmedicated and newly diagnosed patients with PD. The objective of this study was to investigate how common AD biomarkers are in patients with PD and patients with PD and clinical overlapping symptoms. To our knowledge, this study has the largest cohort and is the first to assess CSF AD biomarkers in patients with early PD, depression, and olfactory dysfunction. Among the assessed CSF AD biomarkers, Aβ42 was significantly lower in patients with PD compared to healthy controls, although no alternations of p-tau and t-tau were found. Furthermore, we did not find a significant difference in CSF AD biomarkers between patients with PD and patients with PD and clinical overlapping symptoms. Our results suggest AD pathology is present in early PD; however, the presence of AD pathology could not be further strengthened by the clinical overlapping symptoms.
An Alzheimer-type CSF profile in early Parkinson’s disease
Regarding our first research question, we found an Alzheimer-type CSF profile, indicating that CSF AD biomarkers are common in newly diagnosed patients with PD. The Aβ42-levels were 20% lower in our PD cohort compared to healthy controls, which is in line with studies of varied incidence of PD, ranging from 6% to 24% lower Aβ42-levels (Kang, 2013; Kanemaru, Kameda, & Yamanouchi, 2000; Alves et al. 2010; Compta et al., 2009;
Parnetti et al., 2008). To our knowledge, three studies have examined AD biomarkers in early PD, but only two compared the PD cohort with healthy controls (Terrelonge, Marder, Weintraub, & Alcalay, 2016; Alves et al., 2010). The two studies found that 6% and 19% lower Aβ42-levels in patients with early PD compared to healthy controls (Kang, 2013; Alves et al.
2010). These studies show an inconsistency in effect size, which may be due to the sample-size differences and instrumental differences. Also, Alves et al. (2010) suggest that the heterogeneous nature of PD pathology may be accountable for these inconsistencies. However, our first observation of lower Aβ42-levels suggests that plaque formation be present in early PD (Rambaran & Serpell, 2008; Stav et al., 2015). According to previous studies, plaque formation in PD is associated with future dementia (Siderowf et al., 2010; Alves et al., 2010;
Terrelonge, Marder, Weintraub, & Alcalay, 2016). A several studies also linked lower Aβ42-
levels to cognitive decline (Compta et al., 2011; Alves et al.,2010; Kang, 2013). An additional observation made was that lower MMSE scores in patients with PD compared to healthy controls. This confirms the overall cognitive decline found in PD compared to healthy controls (Aarsland et al., 2009). To conclude our first research question, there is an Alzheimer-type CSF profile reflecting plaques formation in the brain at the time of PD diagnosis. Additionally, lower MMSE scores reflect cognitive decline at the time of diagnosis.
PD-MCI versus PD
Regarding our second research question, we did not find a significant difference in CSF AD biomarkers between patients with PD-MCI and patients with PD, indicating that AD biomarkers are not associated with cognitive decline in early PD. Even though these results differ from Siderowf et al. (2010) and Terrelonge, Marder, Weintraub, & Alcalay (2016), they are consistent with Winer et al. (2018). According to Winer et al. (2018), there is no association between CSF AD biomarkers and patients with PD. However, our non-significant result may also show an AD pathology that has not yet advanced to reflect measurable levels of CSF AD biomarkers. One study found altered CSF-levels of AD biomarkers, two years after baseline (Terrelonge, Marder, Weintraub, & Alcalay, 2016). This is in line with the hypothesis that the alternations may be measurable in later stages of the disease (Parnetti et al., 2008) and with the findings of AD biomarkers in PDD (Irwin, Lee & Trojanowski, 2013). Given the spectrum of cognitive decline ranging from PD-MCI to PDD (Litvan et al., 2012; Dirnberger & Jahanshahi, 2013), the cognitive deficits may not correspond to AD pathology at the time of PD diagnosis.
However, we found a notable non-significant alternation of 17% higher t-tau in patients with PD-MCI compared to PD (p=0,057), reflecting a possible involvement of tau in cognitive decline. Our third observation suggests that AD biomarkers are not associated with newly diagnosed patients with PD-MCI, which may reflect an AD pathology that has not yet advanced to reflect measurable CSF levels.
Most other studies have examined neuropsychological tests in relation to CSF AD biomarkers in patients with PD (Compta et al., 2009; Siderowf et al., 2010; Alves et al., 2010;
Terrelonge, Marder, Weintraub, & Alcalay, 2016). To our knowledge, this study is the first to examine MMSE scores in relation to CSF AD biomarkers in early PD. In our fourth observation, we discovered t-tau and p-tau to be associated with lower MMSE scores. If this observation can be repeated in other studies this might indicate that the spectrum of cognitive decline may correspond to the severity of tau pathology (Litvan et al., 2012; Dirnberger &
Jahanshahi, 2013), which is a contradiction to our third observation. Furthermore, Compta et al. (2012) found that patients with PDD to have lower MMSE scores, as well as higher tau- level, compared to patients with PD-MCI. Our fourth observation suggests that MMSE scores may measure the severity of tau proteins. To conclude our second research question, AD biomarkers are not associated with cognitive decline at the time of PD diagnosis. Additionally, lower MMSE scores measure higher levels of p-tau and t-tau.
Depressed patients versus non-depressed patients
Regarding our third research question, we did not find significant differences in CSF AD biomarkers when comparing depressed patients with PD and non-depressed patients with PD, indicating that AD biomarkers are not associated with depression in PD. To our knowledge, this study is the first to examine CSF AD biomarkers in depressed patients with PD. In research of Alzheimer’s disease, depression is associated with a higher level of neurofibrillary tangles, cognitive decline, and hippocampal changes (Rapp et al., 2008; Rapp et al., 2006). However, our study could not confirm these differences in CSF AD biomarkers
in patients with PD. Previous studies of depression in PD has been associated with multiple neurotransmitter dysfunction (Remy, Doder, Lees, Turjanski, & Brooks, 2005; Postuma et al., 2012). Postuma et al. (2012) suggest the depressive symptoms to be present years before PD diagnosis. However, due to depression being a highly prevalent mood disorder among the general population (World Health Organisation, 2017), it may not serve as a marker for subsequent PD (Postuma et al., 2012). Studies of the etiology of depression suggest a variety of causes that could lead to depression (National Research Council, 2009). Also, we found 39%
of patients of older age to exhibit depression, which confirms previous findings (16%-50%) (Zhu, van Hilten, & Marinus, 2016; Ravina et al., 2007; Ravina et al., 2009). This shows a high prevalence of depression among the PD population, which is associated with older age.
In our fifth observation, we found lower MMSE scores in depressed patients compared to non-depressed patients. These results suggest that depression has a negative impact on cognition, which is in line with Troster et al. (1995) findings. In contrast to our fourth observation (MMSE scores and tau-levels), lower MMSE scores have not shown significantly higher tau-levels in depressed patients. To conclude our third research question, CSF AD biomarkers are not associated with depression at the time of PD diagnosis. In addition, depression has a negative impact on cognitive function, and depressed patients are older than non-depressed patients in PD.
Olfactory dysfunction versus intact olfactory function
Regarding our last (fourth) research question, we did not find an association of CSF AD biomarkers in patients with PD exhibiting olfactory dysfunction compared to patients with PD and intact olfactory function. In our PD cohort, 72% exhibited olfactory dysfunction, which is following the 73% of newly diagnosed patients with PD found by Domellöf, Lundin, Edström, & Forsgren (2017). Olfactory dysfunction and α-syn-levels have been associated with MMSE scores (beach et al., .2010). In the present study, MMSE scores were not significantly different between the patients. The α-syn-levels may not differ as well as levels of Aβ42, p- tau, and t-tau in patients with olfactory dysfunction. It is still unclear how patients with olfactory dysfunction differ from those with intact olfactory function. Other studies have found the future development of PD-MCI and PDD to associate with olfactory dysfunction in PD (Domellöf, Lundin, Edström, & Forsgren, 2017; Gjerde et al., 2018).
Furthermore, the lack of findings in our study may be due to the patients being in an early stage of the disease. Domellöf, Lundin, Edström, & Forsgren (2017) followed the patients over at baseline, 12, 36, 60, and 96 months. A follow-up of our PD cohort is needed to describe the pathological manifestation of olfactory dysfunction. Finally, to conclude our fourth research question, CSF AD biomarkers are not associated with olfactory dysfunction at the time of the PD diagnosis.
Strengths and limitations
The strengths of including a population-based cohort are the strong representativeness and generalisability of the conclusions drawn (Szklo, 1998). The NYPUM and PARKNY cohort included all patients with PD diagnosis from a defined catchment area, which provides a strong external validity of the PD cohort. Furthermore, based on the inclusion criteria and the vast clinical examinations performed on the PD cohort, our study was provided with high coverage (power) and equally distributed data (Szklo, 1998). The screening process of the population involved several health care institutions in Umea, preventing selection bias (Bäckström et al., 2019).
The many clinical assessments that were performed on the PD cohort provides a strong validity, all of which were well-established and standardized (Baek, Kim, Park, & Kim, 2016;
Engedal et al., 2012). The B-SIT test, however, is reported to be influenced by cultural biases (Rodríguez-Violante et al., 2014). Although, this may not affect the internal validity due to the well-defined catchment area limited to Umea, northern Sweden.
First and foremost, the incidence of PD is varying across countries. Ethnic studies found a lower prevalence of PD among Eastern countries compared to Western countries (Abbas, Xu,
& Tan, 2018). It is possible that our results may not reflect PD populations in Eastern countries to the same extent as Western countries. In addition, the criteria for PD diagnosis differs between medical institutions, which could affect the external validity (Muangpaisan, Hori, &
Brayne, 2009). However, the neurologist applied MDS recommendations when diagnosing for PD as well as PD-MCI, which is used internationally (Movement Disorder Society Task Force on Rating Scales for Parkinson’s Disease, 2003).
Furthermore, we combined the PARKNY and NYPUM cohorts. A possible limiation of combining two cohorts could be if variables from one cohort influence the other. For instance, the MDS PD-MCI criteria were set to 1,5 SD – 2 SD during the NYPUM project, whilst during PARKNY project, the PD-MCI criteria were set to 1,0 SD – 1,5 SD. These types of errors were taken into account during the analysis.
We are aware that our research has several limitations. The first is the sample-size difference in the analysis of patients with PD compared to healthy controls, which may have interfered with the validity of the results (Faber & Fonseca, 2014). The second is the PD-MCI re-validation process. We used similar MDS criteria for PD-MCI; however, the re-validation process was conducted through medical records. This may have led to information bias (Groenwold, 2013). A third limitation is the cross-sectional setting, which does not provide a follow-up and may affect the representativeness. Solem (2015) suggests that without longitudinal data, it is difficult to establish the effect of the relationships. In conclusion, these limitations are evidence of the difficulty of collecting and analyzing data that is clinical-based.
In addition, we had power problems with the neuropsychological data, and we did not include α-syn concentration. These two variables would help to clarify some of our research questions, such as CSF AD biomarkers association with olfactory dysfunction in PD.
Future work
At present, there is a lack of studies investigating AD biomarkers in newly diagnosed patients with PD before initiating dopaminergic treatment. However, further investigations need to be carried out on the observed significance in this study. We propose that further work should prospectively investigate whether the early plaque formation has a prognostic value. On a broader level, research is also needed to investigate the manifestation of the overlapping clinical symptoms in PD.
Conclusion
To sum up, our work has led us to the conclusion that AD pathology is present in early PD; however, the presence of AD pathology could not be further strengthened by the overlapping clinical symptoms. Additionally, we found a lower MMSE score associated with higher tau-levels and depressed patients with PD. These findings suggest that the presence of plaques formation in the brain of newly diagnosed patients with PD and lower MMSE scores provides valuable information on possible tau severity. Finally, more prospective studies on newly diagnosed patients with PD need to be carried out to investigate the prognostic values of the presence of AD pathology in PD.
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