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Abstract

Background:

Falls are common among people with idiopathic Parkinson’s disease (IPD) and are suggested to be associated with white matter hyperintensities (WMH) of the brain.

Objective:

To investigate the contribution of brain area-specific WMH to the risk of falls in IPD.

Methods:

In fifty participants with IPD, occurrence and severity of WMH in specific brain areas were determined using Scheltens (without lateralization) and Age-related white matter changes (ARWMC) (with lateralization) scores. Falls were evaluated with the fall item of the Unified PD Rating Scale (UPDRS). Correlations between area-specific WMH and falls were tested with stepwise backward regression and multivariate regression analyses.

Results:

In this cohort of participants with IPD, left temporal WMH were associated with occurrence of falls. Frontal WMH of both hemispheres showed tendencies towards significance for the association with falls.

Conclusion:

According to our study, WMH in the left temporal area are significantly associated with falls in IPD. Potential reasons for this association could be deficits in memory, navigation, orientation, auditory processing, and fear conditioning, which are all associated with pathologies of the left temporal lobe.

Keywords

Accidental falls leukoencephalopathies temporal lobe

INTRODUCTION

Falls lead to fractures and fear of falling especially in older adults, and cause severe consequences regarding social participation and quality of life [1 –3]. The events contribute to immobilization, in turn increasing the risk of cardiovascular diseases, such as stroke [4, 5], and cognitive deterioration [6]. Patients with idiopathic Parkinson’s disease (IPD) are at increased risk of falling, e.g., due to postural instability, bradykinesia, and rigidity [7]. Both in older adults and IPD patients, white matter hyperintensities (WMH) represent a relevant risk factor for falls [8 –11]. WMH are single or confluent hyperintense areas on T2- or T2-FLAIR- (fluid-attenuated inversion recovery) weighted cranial MRI images of the subcortical, periventricular and deep white matter (in advanced disease stages, the basal ganglia, thalami, the brain stem and cerebellar white matter are included). These WMH are due to neuronal demyelinisation and axonal damage caused by cerebral microangiopathy [12]. The association is not entirely clear; however, it is probable that WMH influence the integrity of complex central networks, resulting in gait, balance, and cognitive deficits [8, 13]. There is evidence that WMH in periventricular, deep frontal, and parietal areas are relevant for balance and gait deficits in older adults, and are associated with falls [14 –16]. As IPD patients have a clinical status different from the general older population due to their motor and non-motor profile, WMH may have different effects. However, studies performed in IPD regarding brain area-specific WMH and their contribution to falls risk are scarce. One study compared WMH in different brain areas of 110 participants with IPD, and did not find a significant correlation between brain-area-specific WMH and number of falls [17]. Lateralization aspects were not tested in that study.

This is, to our best knowledge, the first study investigating the association between falls and area-specific WMH in IPD considering lateralization aspects of the WMH.

SUBJECTS AND METHODS

Participants

This cross-sectional exploratory study was conducted between 04/2014 and 05/2015 at the Neurology Department of the University Hospital Tuebingen. Inclusion criteria were age between 50 and 85 years, diagnosis of an IPD according to the UK Brain-Bank-Criteria [18], the ability and willingness to communicate with the examiners and to understand the requirements of the study, existence of a recent axial T2- or FLAIR-weighted cerebral MRI sequence done in clinical routine, and obtainment of written informed consent. Exclusion criteria were neuroimmunological or neurooncological diseases, neurodegenerative diseases other than IPD, dementia according to the International Classification of Diseases-10 (ICD-10), other limitations preventing the participant from giving her/his consent or understanding the requirements of the study, and history of substance abuse with the exception of nicotine. Fifty participants who met the above-mentioned criteria were included. One participant had arthrosis of the hip (no surgical treatment) and two had arthrosis of the knees (one with knee replacement). One participant had atrial fibrillation. Moreover, 20% had hypercholesterolemia, 36% hypertension, 4% (asymptomatic) coronary heart disease and 8% had type II diabetes. Concerning medication related to falls [19 –21], 40% were taking antidepressants, 12% atypical antipsychotic medication and 2% benzodiazepines. The study was approved by the ethical committee of the Medical Faculty at the University of Tuebingen (No 686/2013BO1). Table 1 shows demographic and clinical parameters of the cohort.

Table 1

Demographic, clinical and “overall” MRI parameters

	Non-Fallers	Fallers	Whole cohort
	M (range)	M (range)	M (range)
Number (female)	32 (10)	18 (9)	50 (19)
Age [years]	67.5 (49–75)	70 (58–77)	69 (50–77)
Age at disease onset [years]	61 (36–74)	62 (49–75)	61 (36–75)
Disease duration [years]	6.07 (0.47–21)	5.65 (0.01–12.84)	6 (0.01–21)
MoCA (0–30)	25 (17–30)	27 (17–30)	25 (17–30)
Total MDS-UPDRS (0–260)	53 (27–126)	56 (35–84)	56 (27–126)
MDS-UPDRS-III (0–132)	28 (13–58)	32 (9–43)	30 (9–58)
MDS-UPDRS item “freezing”≥1 [Number (%)]	11 (34)	8 (44)	19 (38)
BDI-II (0–63)	10 (0–32)	11 (2–36)	10 (0–36)
LED [mg]	605 (130–2530)	640 (200–2419)	605 (130–2530)
Fear of falling (0–4)	0 (0–4)	1 (0–3)	1 (0–4)
Hoehn and Yahr stage (1–5)	2 (1–4)	2 (1–3)	2 (1–4)
Scheltens total score (0–84)	5 (0–18)	6 (0–18)	6 (0–18)
ARWMC total score (0–30)	2 (0–10)	2 (0–12)	2 (0–12)
Use of antidepressants [Number (%)]	14 (44)	6 (33)	20 (40)
Use of benzodiazepines [Number (%)]	1 (3)	0	1 (2)
Use of atypical antipsychotics [Number (%)]	4 (13)	2 (11)	6 (12)
Atrial fibrillation [Number (%)]	0	1 (6)	1 (2)
Arthrosis of the hip [Number (%)]	0	1 (6)	1 (2)
Arthrosis of the knees [Number (%)]	1 (3)	1 (6)	2 (4)
Hypercholesterolemia [Number (%)]	6 (19)	4 (22)	10 (20)
Hypertension [Number (%)]	8 (25)	10 (56)	18 (36)
Coronary heart disease [Number (%)]	0	2 (11)	2 (4)
Type II diabetes [Number (%)]	2 (6)	2 (11)	4 (8)

ARWMC, Age Related White Matter Changes; BDI-II, Beck Depression Inventory II; IPD, Idiopathic Parkinson’s Disease; LED, Levodopa equivalent dosage; M, median; MDS-UPDRS, Movement Disorder Society-Sponsored Revision of the Unified Parkinson’s Disease Rating Scale; MoCA, Montreal Cognitive Assessment; N, number.

Clinical assessment

Occurrence of falls during the last four weeks was retrospectively assessed using the fall item of the Unified Parkinson’s Disease Rating Scale [22] (UPDRS-I-13), with scoring as follows: 0 = none; 1 = rare falling; 2 = occasionally falls, less than once per day; 3 = falls an average of once daily; 4 = falls more than once daily. For the exploration of the participants, the ProFANE definition of a fall was used: an unexpected event in which the participants come to rest on the ground, floor, or lower level [23]. Participants with 0 points were defined as non-fallers, participants with 1–4 points as fallers.

The clinical assessment of the participants also included the assessment of cognition using the Montreal Cognitive Assessment (MoCA) [24], severity of depressive symptoms with the Beck Depression Inventory II (BDI II) [25], health-related quality of life with the 39-item Parkinson’s Disease Questionnaire [26] (PDQ-39), and motor performance via the motor part of the revised version of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS III) [27]. Participants were assessed during the ‘ON’ medication state.

Assessment of white matter hyperintensities

WMH were rated on axial T2- or T2-FLAIR-weighted images from cranial MRIs performed during routine clinical assessment using the Scheltens [28] and Age-related white matter changes (ARWMC) Scores [29, 30]. The Scheltens score enables a detailed semiquantitative rating, registering the severity of WMH via subscores for specific brain areas without considering right/left differences. The ARWMC score differentiates between specific brain areas of right and left hemispheres. An examiner trained in both scores and blinded to the clinical status of the participants (MC) rated the cranial MRIs of all participants accordingly.

Statistics

Statistical analysis was performed with JMP® version 11.2.0. Demographic, clinical, and radiological parameters of non-fallers and fallers were calculated using median and range, or frequency. Associations of WMH in specific brain regions with falls were determined in the total cohort with a stepwise backward regression, and the corrected coefficient of determination r² was defined. In case of significant results, a regression analysis with the area of interest in combination with the following potential confounders was performed: age [31 –33], cognition [34, 35] (MoCA), severity of depressive symptoms [36 –38] (BDI-II), fear of falling [39, 40] (PDQ-39 item), and motor deficits [41, 42] (MDS-UPDRS-III). The corrected coefficients of determination r² and the p-values are reported. A p-value <0.05 was considered significant.

RESULTS

Table 1 provides details about demographic, clinical, and “overall” WMH parameters of non-fallers and fallers. As a general note, these groups did not relevantly differ with regard to the above-mentioned parameters.

Scheltens score

The corrected coefficient of determination between (non-lateralized but area-specific) WMH and falls was r² = 0.00. The stepwise backward model removed all areas from the list. None of the areas proved themselves associated to falls. There was no significant association between falls and total WMH (p = 0.35).

ARWMC score

The corrected coefficient of determination between lateralized area-specific WMH and falls was r² = 0.14. This means that WMH in hemispheric-dependent areas explained 14% of the presence versus absence of falls. The stepwise backward model removed all but three areas: left temporal, left frontal and right frontal.

Subsequent regression analyses with these three areas in combination with potential confounders (age, cognition (MoCA), severity of depressive symptoms (BDI-II), fear of falling (PDQ-39 item), and motor deficits (MDS-UPDRS-III)) revealed the following results: in the regression analysis for left temporal WMH, the six factors explained 23% of presence versus absence of falls. In this analysis, left temporal WMH were also associated with occurrence of falls (p = 0.004). Additionally, age and MoCA-Score were significantly associated with presence of falls. In the regression analysis for left frontal WMH, the factors explained 14% of the falls. The left frontal WMH themselves did not correlate with presence of falls (p = 0.66), but the MoCA-Score did. Comparably, in the regression analysis for right frontal WMH, the factors explained 10% of the falls. Again, the right frontal WMH did not significantly correlate with presence of falls (p = 0.20), but age and MoCA-Score did. Details are presented in Table 2. We did again not observe a significant association between falls and total WMH (p = 0.50).

Table 2

Associations between falls and white matter hyperintensities (WMH) of the left temporal (A), left frontal (B) and right frontal areas (C) with ARWMC score, including influence of potential confounders

A: WMH of the left temporal area and falls	95% CI	p-value
Total r² corrected: 0.23
Left temporal WMH	0.20–0.97	0.004
Age	0–0.04	0.045
MoCA	0.02–0.11	0.003
BDI II	0–0.02	0.32
Fear of falling	– 0.09–0.19	0.48
MDS-UPDRS-III	– 0.02–0.01	0.38
B: WMH of the left frontal area and falls
Total r² corrected: 0.14
Left frontal WMH	– 0.20–0.31	0.66
Age	0–0.05	0.07
MoCA	0–0.09	0.047
BDI II	– 0.01–0.02	0.48
Fear of falling	– 0.11–0.21	0.53
MDS-UPDRS-III	– 0.02–0.01	0.66
C: WMH of the right frontal area and falls
Total r² corrected: 0.10
Right frontal WMH	– 0.35–0.08	0.20
Age	0–0.05	0.022
MoCA	0–0.09	0.031
BDI II	– 0.01–0.02	0.59
Fear of falling	– 0.07–0.25	0.26
MDS-UPDRS-III	– 0.02–0.01	0.56

Correlation coefficients were calculated with regression analysis. P-values <0.05 are presented in bold. ARWMC, Age Related White Matter Changes; BDI II, Beck Depression Inventory II; MDS-UPDRS, Movement Disorder Society-Sponsored Revision of the Unified Parkinson’s Disease Rating Scale; MoCA, Montreal Cognitive Assessment.

DISCUSSION

This exploratory study investigated the association of lateralized and non-lateralized area-specific WMH with the presence of falls in an IPD cohort. The analysis was motivated by previous findings describing associations of motor and balance deficits with periventricular [14, 15], deep frontal [15], and parietal [16] WMH in healthy older adults. A possible explanation for these findings could be that these “strategically located” WMH interrupt corticospinal circuits responsible for gait and balance performance [10]. Such strategic lesions may be particularly relevant for diseases of the central motor system, such as IPD, and need further investigation. In fact, a previous study investigated -hemisphere-independent- correlations of WMH with falls in IPD, but did not find significant results [17]. We thus hypothesized that not area-specific but rather lateralized WMH are associated with the occurrence of falls in IPD.

We could confirm results of the previous IPD study [17] insofar as we did not find hemispheric-independent brain areas associated with falls. However, lateralized area-specific WMH of the left temporal area showed a significant association with falls in IPD, even after correction for confounders known to contribute considerably to increased fall risk in IPD. This result is intriguing due to a number of reasons. First, auditory processing is mainly performed in the temporal lobe and is left hemisphere-dominant in the majority of cases [43]. Moreover, hearing deficits have been associated with falls in a recent study [44]. Second, the hippocampus and amygdala belong to the temporal lobe and are included in orientation and memory functions. A recent study [45] showed that, compared to non-fallers, fallers have worse orientation and memory functions. Third, the hippocampus is strongly associated with navigation capability [46], and there is increasing evidence that the left hippocampus is particularly relevant for gait control, especially during difficult walking situations [47]. Fourth, the amygdala, localized in the temporal lobe, is responsible for conditioning of fear [48], and there is evidence that the left amygdala is especially responsible for conscious cognitive processing (whereas the right amygdala is responsible for automatic emotional processing) [49]. Consequently, the impairment of the left amygdala or its circuits can cause a miscalculation of situations associated with fearful conscious processes, such as fear of falling and the attempt of maintaining balance. Finally, as (i) PD is associated with cholinergic deficits [50], (ii) cholinergic deficits particularly in PD trigger postural instability and occurrence of falls [51, 52], and (iii) there is evidence that the left temporal lobe has a higher acetylcholine production than the right temporal lobe [53], it is intriguing to hypothesize that the PD-associated cholinergic deficit may contribute to our findings.

Left frontal and right frontal WMH remained in our first statistical model for association with falls and thus may also have some association with fall events. Based on previous literature, such an association is possible. It has been shown that the interruption of fronto-subcortical circuits via WMH leads to increased fall risk via executive dysfunction [54]. Still, after correction for multiple confounders the areas no longer contributed to fall occurrence, thus future studies with larger cohort sizes may clarify whether WMH in frontal areas also contribute to fall risk in IPD.

This study confirms the already known influence of cognition and age on the occurrence of falls [39 , 55]. The association of falls with age can be best explained by age-related comorbidities, such as visual deficits [56], osteoarthritis [57], and arrhythmia [58]. The association of falls with cognition may be best explained by specific cognitive deficits that have already been demonstrated to be associated with postural instability and falls, such as dual-tasking [59], orientation [45], attention [60], and memory [45]. In our regression analyses, six factors including cognition and age explained 10–23% of presence versus absence of falls. Although these results highlight the relevance of the above-mentioned factors, the large variance that remains unexplained motivates further research on potential fall-contributing factors.

This exploratory study faces some limitations. First, the investigated cohort is relatively small and we did not include a control group of “healthy” older adults. Therefore, our results should be re-evaluated in a larger and controlled cohort. Second, falls were defined by retrospective evaluation with a relatively simple fall assessment tool and no detailed information about the cause and circumstances of falls (e.g., depression [61], orthostatic hypotension and syncope [62], freezing of gait [63]) was included in our analysis. We also did not consider medication aspects in the analyses. These aspects may influence the accuracy of our results. Future studies with more reliable falls assessment approaches including prospective designs [41] and quantitative analysis methods (such as wearable sensors [64]) are certainly necessary. Third, WMH were analysed using semi-quantitative scales. Although they represent a validated method, quantitative volumetric measurements can yield more objective and detailed results. Fourth, we are aware of the fact that this study did not include all confounding factors for falls in PD that are currently known; however, the aim of this study was to define potentially contributing brain areas by using a statistical approach taking explicitly relevant confounding factors into account. We argue that, despite these limitations, this pilot study has relevant hypothesis-generating potential and should motivate a more detailed evaluation of the interaction of WMH and falls in this vulnerable cohort.

In conclusion, our results suggest that left temporal WMH increase fall risk in people with IPD. This result is intriguing due to the representation of features that substantially contribute to safe walking especially under challenging conditions, such as memory, navigation, orientation, auditory processing, and fear conditioning.

CONFLICT OF INTEREST

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Footnotes

ACKNOWLEDGMENTS

We thank all participants of the study.

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Brain-Area Specific White Matter Hyperintensities: Associations to Falls in Parkinson’s Disease

Abstract

Background:

Objective:

Methods:

Results:

Conclusion:

Keywords

INTRODUCTION

SUBJECTS AND METHODS

Participants

Clinical assessment

Assessment of white matter hyperintensities

Statistics

RESULTS

Scheltens score

ARWMC score

DISCUSSION

CONFLICT OF INTEREST

Footnotes

ACKNOWLEDGMENTS

References