The Gut Dysmotility Questionnaire for Parkinson's disease: Insights into development and pretest studies.

Objective: A total of 48% of patients with Parkinson's disease (PD) present symptoms of gastrointestinal dysfunction, particularly constipation. Furthermore, gastrointestinal tract (GIT)-related non-motor symptoms (NMSs) appear at all stages of PD, can be prodromal by many years and have a relevant impact on the quality of life. There is a lack of GIT-focused validated tools specific to PD to assess their occurrence, progress, and response to treatment. The aim of this study was to develop and evaluate a novel, disease- and symptom-specific, self-completed questionnaire, titled Gut Dysmotility Questionnaire (GDQ), for screening and monitoring gastrointestinal dysmotility of the lower GIT in patients with PD. Methods: In phase 1, a systematic literature review and multidisciplinary expert discussions were conducted. In phase 2, cognitive pretest studies comprising standard pretests, interviews, and evaluation questionnaires were performed in patients with PD (n = 21), age- and sex-matched healthy controls (HC) (n = 30), and neurologists (n = 11). Incorporating these results, a second round of cognitive pretests was performed investigating further patients with PD (n = 10), age- and sex-matched HC (n = 10), and neurologists (n = 5). The questionnaire was adapted resulting in the final GDQ, which underwent cross-cultural adaptation to the English language. Results: We report significantly higher GDQ total scores and higher scores in five out of eight domains indicating a higher prevalence of gastrointestinal dysmotility in patients with PD than in HC (p < 0.05). Cognitive pretesting improved the preliminary GDQ so that the final GDQ was rated as relevant (100/100%), comprehensive (100/90%), easy to understand concerning questions and answer options (100/90%), and of appropriate length (80/100%) by neurologists and patients with PD, respectively. The GDQ demonstrated excellent internal consistency (Cronbach's alpha value of 0.94). Evidence for good construct validity is given by moderate to high correlations of the GDQ total score and its domains by intercorrelations (r s = 0.67-0.91; p < 0.001) and with validated general NMS measures as well as with specific items that assess gastrointestinal symptoms. Interpretation: The GDQ is a novel, easy, and quick 18-item self-assessment questionnaire to screen for and monitor gastrointestinal dysmotility with a focus on constipation in patients with PD. It has shown high acceptance and efficacy as well as good construct validity in cognitive pretests.

Novel Cell-Based Assay for Alpha-3 Nicotinic Receptor Antibodies Detects Antibodies Exclusively in Autoimmune Autonomic Ganglionopathy.

BACKGROUND AND OBJECTIVES: Autoantibodies against α3-subunit-containing nicotinic acetylcholine receptors (α3-nAChRs), usually measured by radioimmunoprecipitation assay (RIPA), are detected in patients with autoimmune autonomic ganglionopathy (AAG). However, low α3-nAChR antibody levels are frequently detected in other neurologic diseases with questionable significance. Our objective was to develop a method for the selective detection of the potentially pathogenic α3-nAChR antibodies, seemingly present only in patients with AAG. METHODS: The study involved sera from 55 patients from Greece, suspected for autonomic failure, and 13 patients from Italy diagnosed with autonomic failure, positive for α3-nAChR antibodies by RIPA. In addition, sera from 52 patients with Ca2+ channel or Hu antibodies and from 2,628 controls with various neuroimmune diseases were included. A sensitive live cell-based assay (CBA) with α3-nAChR-transfected cells was developed to detect antibodies against the cell-exposed α3-nAChR domain. RESULTS: Twenty-five patients were found α3-nAChR antibody positive by RIPA. Fifteen of 25 patients were also CBA positive. Of interest, all 15 CBA-positive patients had AAG, whereas all 10 CBA-negative patients had other neurologic diseases. RIPA antibody levels of the CBA-negative sera were low, although our CBA could detect dilutions of AAG sera corresponding to equally low RIPA antibody levels. No serum bound to control-transfected cells, and none of the 2,628 controls was α3-CBA positive. DISCUSSION: This study showed that in contrast to the established RIPA for α3-nAChR antibodies, which at low levels is of moderate disease specificity, our CBA seems AAG specific, while at least equally sensitive with the RIPA. This study provides Class II evidence that α3-nAChR CBA is a specific assay for AAG. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that an α3-nAChR cell-based assay is a more specific assay for AAG than the standard RIPA.

Parkinson's Disease Detection Based on Running Speech Data From Phone Calls.

OBJECTIVE: Parkinson's Disease (PD) is a progressive neurodegenerative disorder, manifesting with subtle early signs, which, often hinder timely and early diagnosis and treatment. The development of accessible, technology-based methods for longitudinal PD symptoms tracking in daily living, offers the potential for transforming disease assessment and accelerating diagnosis. METHODS: A privacy-aware method for classifying patients and healthy controls (HC), on the grounds of speech impairment present in PD, is proposed. Voice features from running speech signals were extracted from passively-captured recordings over voice calls. Language-aware training of multiple- and single-instance learning classifiers was employed to fuse and predict on voice features and demographic data from a multilingual cohort of 498 subjects (392/106 self-reported HC/PD patients). RESULTS: By means of leave-one-subject-out cross-validation, the best-performing models yielded 0.69/0.68/0.63/0.83 area under the Receiver Operating Characteristic curve (AUC) for the binary classification of PD patient vs. HC in sub-cohorts of English/Greek/German/Portuguese-speaking subjects, respectively. Out-of sample testing of the best performing models was conducted in an additional dataset, generated by 63 clinically-assessed subjects (24/39 HC/early PD patients). Testing has resulted in 0.84/0.93/0.83 AUC for the English/Greek/German-speaking sub-cohorts, respectively. CONCLUSIONS: The proposed approach outperforms other methods proposed for language-aware PD detection considering the ecological validity of the voice data. SIGNIFICANCE: This paper introduces for the first time a high-frequency, privacy-aware and unobtrusive PD screening tool based on analysis of voice samples captured during routine phone calls.

Smartwatch-based Activity Analysis During Sleep for Early Parkinson's Disease Detection.

Parkinson's Disease (PD) is the second most common neurodegenerative disorder with the non-motor symptoms preceding the motor impairment that is needed for clinical diagnosis. In the current study, an angle-based analysis that processes activity data during sleep from a smartwatch for quantification of sleep quality, when applied on controls and PD patients, is proposed. Initially, changes in their arm angle due to activity are captured from the smartwatch triaxial accelerometry data and used for the estimation of the corresponding binary state (awake/sleep). Then, sleep metrics (i.e., sleep efficiency index, total sleep time, sleep fragmentation index, sleep onset latency, and wake after sleep onset) are computed and used for the discrimination between controls and PD patients. A process of validation of the proposed approach when compared with the PSG-based ground truth in an in-the-clinic setting, resulted in comparable state estimation. Moreover, data from 15 early PD patients and 11 healthy controls were used as a test set, including 1,376 valid sleep recordings in-the-wild setting. The univariate analysis of the extracted sleep metrics achieved up to 0.77 AUC in early PD patients vs. healthy controls classification and exhibited a statistically significant correlation (up to 0.46) with the clinical PD Sleep Scale 2 counterpart Items. The findings of the proposed method show the potentiality to capture non-motor behavior from users' nocturnal activity to detect PD in the early stage.

Screening of Parkinsonian subtle fine-motor impairment from touchscreen typing via deep learning.

Fine-motor impairment (FMI) is progressively expressed in early Parkinson's Disease (PD) patients and is now known to be evident in the immediate prodromal stage of the condition. The clinical techniques for detecting FMI may not be robust enough and here, we show that the subtle FMI of early PD patients can be effectively estimated from the analysis of natural smartphone touchscreen typing via deep learning networks, trained in stages of initialization and fine-tuning. In a validation dataset of 36,000 typing sessions from 39 subjects (17 healthy/22 PD patients with medically validated UPDRS Part III single-item scores), the proposed approach achieved values of area under the receiver operating characteristic curve (AUC) of 0.89 (95% confidence interval: 0.80-0.96) with sensitivity/specificity: 0.90/0.83. The derived estimations result in statistically significant ([Formula: see text]) correlation of 0.66/0.73/0.58 with the clinical standard UPDRS Part III items 22/23/31, respectively. Further validation analysis on 9 de novo PD patients vs. 17 healthy controls classification resulted in AUC of 0.97 (0.93-1.00) with 0.93/0.90. For 253 remote study participants, with self-reported health status providing 252.000 typing sessions via a touchscreen typing data acquisition mobile app (iPrognosis), the proposed approach predicted 0.79 AUC (0.66-0.91) with 0.76/0.71. Remote and unobtrusive screening of subtle FMI via natural smartphone usage, may assist in consolidating early and accurate diagnosis of PD.

Assistive HCI-Serious Games Co-design Insights: The Case Study of i-PROGNOSIS Personalized Game Suite for Parkinson's Disease.

Human-Computer Interaction (HCI) and games set a new domain in understanding people's motivations in gaming, behavioral implications of game play, game adaptation to player preferences and needs for increased engaging experiences in the context of HCI serious games (HCI-SGs). When the latter relate with people's health status, they can become a part of their daily life as assistive health status monitoring/enhancement systems. Co-designing HCI-SGs can be seen as a combination of art and science that involves a meticulous collaborative process. The design elements in assistive HCI-SGs for Parkinson's Disease (PD) patients, in particular, are explored in the present work. Within this context, the Game-Based Learning (GBL) design framework is adopted here and its main game-design parameters are explored for the Exergames, Dietarygames, Emotional games, Handwriting games, and Voice games design, drawn from the PD-related i-PROGNOSIS Personalized Game Suite (PGS) (www.i-prognosis.eu) holistic approach. Two main data sources were involved in the study. In particular, the first one includes qualitative data from semi-structured interviews, involving 10 PD patients and four clinicians in the co-creation process of the game design, whereas the second one relates with data from an online questionnaire addressed by 104 participants spanning the whole related spectrum, i.e., PD patients, physicians, software/game developers. Linear regression analysis was employed to identify an adapted GBL framework with the most significant game-design parameters, which efficiently predict the transferability of the PGS beneficial effect to real-life, addressing functional PD symptoms. The findings of this work can assist HCI-SG designers for designing PD-related HCI-SGs, as the most significant game-design factors were identified, in terms of adding value to the role of HCI-SGs in increasing PD patients' quality of life, optimizing the interaction with personalized HCI-SGs and, hence, fostering a collaborative human-computer symbiosis.

Identification of clinically related requirements of a novel assistive device for people with a high spinal cord injury.

People with spinal cord injuries (SCI), and particularly with high level lesions, can potentially lose the ability to effectively operate computers. The Multimedia Authoring and Management using your Eyes and Mind (MAMEM) project aims to design and produce a novel assistive device to support computer use by individuals with SCI and other disabilities. The solution harnesses eye tracking and brain waves, as measured by encephalography (EEG), to manipulate common computer functions. This paper describes the first step in the project, during which we defined clinically related requirements of the assistive device. These definitions were based on data from three sources: (1) a narrative review; (2) a focus group of SCI rehabilitation professionals; and (3) structured questionnaires administrated to potential computer users with SCI, addressing computer-use habits, barriers, and needs. We describe both the collection of data from each source and the clinically related requirements extracted. The novel three-source requirement assessment method is discussed, and the advantages and disadvantages of each data source are reported. In conclusion, we suggest that this approach makes it possible to organize, discuss, and prioritize the requirements, and to create a work program while planning the device. This increases our level of certainty that the efficacy and adequacy of the assistive device will be maximized, in terms of the clinical needs of users.

Early Parkinson's Disease Detection via Touchscreen Typing Analysis using Convolutional Neural Networks.

Parkinson's Disease (PD) is the second most common neurodegenerative disorder worldwide, causing both motor and non-motor symptoms. In the early stages, symptoms are mild and patients may ignore their existence. As a result, they do not undergo any related clinical examination; hence delaying their PD diagnosis. In an effort to remedy such delay, analysis of data passively captured from user's interaction with consumer technologies has been recently explored towards remote screening of early PD motor signs. In the current study, a smartphone-based method analyzing subjects' finger interaction with the smartphone screen is developed for the quantification of fine-motor skills decline in early PD using Convolutional Neural Networks. Experimental results from the analysis of keystroke typing in-the-clinic data from 18 early PD patients and 15 healthy controls have shown a classification performance of 0.89 Area Under the Curve (AUC) with 0.79/0.79 sensitivity/specificity, respectively. Evaluation of the generalization ability of the proposed approach was made by its application on typing data arising from a separate self-reported cohort of 27 PD patients' and 84 healthy controls' daily usage with their personal smartphones (data in-the-wild), achieving 0.79 AUC with 0.74/0.78 sensitivity/specificity, respectively. The results show the potentiality of the proposed approach to process keystroke dynamics arising from users' natural typing activity to detect PD, which contributes to the development of digital tools for remote pathological symptom screening.

Two Novel KRIT1 and CCM2 Mutations in Patients Affected by Cerebral Cavernous Malformations: New Information on CCM2 Penetrance.

Wide comprehension of genetic features of cerebral cavernous malformations (CCM) represents the starting point to better manage patients and risk rating in relatives. The causative mutations spectrum is constantly growing. KRIT1, CCM2, and PDCD10 are the three loci to date linked to familial CCM development, although germline mutations have also been detected in patients affected by sporadic forms. In this context, the main challenge is to draw up criteria to formulate genotype-phenotype correlations. Clearly, genetic factors determining incomplete penetrance of CCM need to be identified. Here, we report two novel intronic variants probably affecting splicing. Molecular screening of CCM genes was performed on DNA purified by peripheral blood. Coding exons and intron-exon boundaries were sequenced by the Sanger method. The first was detected in a sporadic patient and involves KRIT1. The second affects CCM2 and it is harbored by a woman with familial CCM. Interestingly, molecular analysis extended to both healthy and ill relatives allowed to estimate, for the first time, a penetrance for CCM2 lower than 100%, as to date reported. Moreover, heterogeneity of clinical manifestations among those affected carrying the same genotype further confirms involvement of modifier factors in CCM development.

Touchscreen typing-pattern analysis for detecting fine motor skills decline in early-stage Parkinson's disease.

Parkinson's disease (PD) is a degenerative movement disorder causing progressive disability that severely affects patients' quality of life. While early treatment can produce significant benefits for patients, the mildness of many early signs combined with the lack of accessible high-frequency monitoring tools may delay clinical diagnosis. To meet this need, user interaction data from consumer technologies have recently been exploited towards unsupervised screening for PD symptoms in daily life. Similarly, this work proposes a method for detecting fine motor skills decline in early PD patients via analysis of patterns emerging from finger interaction with touchscreen smartphones during natural typing. Our approach relies on low-/higher-order statistical features of keystrokes timing and pressure variables, computed from short typing sessions. Features are fed into a two-stage multi-model classification pipeline that reaches a decision on the subject's status (PD patient/control) by gradually fusing prediction probabilities obtained for individual typing sessions and keystroke variables. This method achieved an AUC = 0.92 and 0.82/0.81 sensitivity/specificity (matched groups of 18 early PD patients/15 controls) with discriminant features plausibly correlating with clinical scores of relevant PD motor symptoms. These findings suggest an improvement over similar approaches, thereby constituting a further step towards unobtrusive early PD detection from routine activities.

The cortical excitability profile of patients with the G209A SNCA mutation versus patients with sporadic Parkinson's disease: A transcranial magnetic stimulation study.

Mutations in the α-synuclein gene are a rare cause of Parkinson's disease. We investigated, by single-pulse TMS, the cortical excitability profile of nine α-synuclein patients in comparison with 24 idiopathic PD patients, subdivided into "akinetic" (n=17) and "tremor-dominant" (n=7) subgroups. The comparative assessment of rest motor threshold, active MEP and Silent Period Input/Output curves indicated that the cortical excitability of α-Synuclein patients is similar to patients with the "akinetic" form of PD. Both groups of patients exhibited differences in excitatory and inhibitory brain circuits from "tremor-dominant" patients indicating that varying clinical phenotypes are associated with differential profiles of corticospinal excitability.

A multimodal dataset for authoring and editing multimedia content: The MAMEM project.

We present a dataset that combines multimodal biosignals and eye tracking information gathered under a human-computer interaction framework. The dataset was developed in the vein of the MAMEM project that aims to endow people with motor disabilities with the ability to edit and author multimedia content through mental commands and gaze activity. The dataset includes EEG, eye-tracking, and physiological (GSR and Heart rate) signals collected from 34 individuals (18 able-bodied and 16 motor-impaired). Data were collected during the interaction with specifically designed interface for web browsing and multimedia content manipulation and during imaginary movement tasks. The presented dataset will contribute towards the development and evaluation of modern human-computer interaction systems that would foster the integration of people with severe motor impairments back into society.

D620N mutation in the VPS35 gene and R1205H mutation in the EIF4G1 gene are uncommon in the Greek population.

Recently, vacuolar protein sorting 35 (VPS35) and eukaryotic translation initiation factor 4 gamma 1 (EIF4G1) have been identified as new causal Parkinson's disease (PD) genes, with the VPS35 D620N and EIF4G1 R1205H mutations being identified in both autosomal dominant late-onset familial and sporadic PD patients. However, the frequencies of these two mutations among different ethnic groups vary. We studied the VPS35 D620N and EIF4G1 R1205H mutations in a total of 333 individuals, 202 Greek patients with sporadic PD and 131 control subjects, using a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. None of our studied individuals carried these two mutations. Our data support that the VPS35 D620N and EIF4G1 R1205H mutations are not a common cause of PD in the Greek population.

Detection of Novel Mutation in Ccm3 Causes Familial Cerebral Cavernous Malformations.

Cerebral cavernous malformations are vascular lesions that usually involve brain micro-vessels. They can occur both in a sporadic form and familial one. Causes of familial forms are mutations at three loci: CCM1/KRIT1, CCM2/MGC4607, and CCM3/PDCD10. Here, we describe a novel CCM3 missense mutation (c.422T>G) detected in two Greek brothers showing multiple lesions at magnetic resonance imaging; to date, only the youngest is symptomatic. Bioinformatics tools showed this novel variant causes a loss of function in Pdcd10 protein due to its localization in the eighth helix and, particularly, affects Leu141, a highly conserved amino acid. Roles of Pdcd10 in angiogenesis regulation and its association with early development of cerebral cavernous malformations were also considered.

Clinical characteristics of Parkinson's disease patients in Greece: a multicenter, nation-wide, cross-sectional study.

Parkinson's disease is a neurodegenerative disease, with a constantly increasing prevalence and a high global financial impact arising from direct and indirect costs. Large-scale, observational studies provide data that support the better comprehension of disease aspects, constitute a baseline reference for future studies and assist comparisons among different patient populations, allowing the recognition of distinctive characteristics and special needs. The present study is the first to depict the clinical characteristics and their interplay in a large sample of Parkinson's disease (PD) patients in Greece. Nine hundred eighty six consecutive PD outpatients were recruited from 17 centers around Greece in the time period from 8/2007 to 7/2009 and were examined and interviewed by movement disorders experts. Multiple clinical characteristics were recorded including age at diagnosis, disease severity, patients' self classification of PD symptoms and their relevance to physician's global clinical impression, smoking, alcohol consumption, presence of family history for PD, dementia, depression, hypertension, cancer and other comorbidities. Associations of high clinical significance were found between certain clinical characteristics.

Association study of rs6812193 polymorphism with Parkinson's disease in a Greek population.

In a recent web based genome-wide association study (GWA) the rs6812193 polymorphism was identified as a new risk factor for Parkinson's disease (PD). The purpose of our study was to examine the association of the rs6812193 polymorphism with Parkinson's disease (PD) in case-control association study of Greek individuals. We studied a total of 343 individuals, 210 Greek patients with sporadic PD and 133 control subjects, using a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. We found no differences in genotype or allele frequencies between PD patients and controls (P=0.795 and P=0.892, respectively), suggesting that the rs6812193 polymorphism does not increase susceptibility to PD in the Greek population. Additional studies further investigating the association of the rs6812193 polymorphism with PD are needed in order to clarify the role of this polymorphism in different ethnicities.

TLR9 -1237 T/C and TLR2 -194 to -174 del polymorphisms and the risk of Parkinson's disease in the Greek population: a pilot study.

Toll-like receptors (TLRs) are important mediators of inflammatory responses by recognition of many pathogen-related molecules and endogenous proteins related to immune activation. Accumulating data have recently pointed out the role of neuroinflammation in Parkinson's disease (PD) pathogenesis. In the present study, we investigated the potential role of the TLR9 -1237 T/C and TLR2 -194 to -174 del polymorphisms in PD. We studied a total of 333 individuals, 215 Greek patients with sporadic PD and 118 control subjects, using a polymerase chain reaction-restriction fragment length polymorphism method. No statistically significant differences were found between PD patients and control subjects for the TLR9 -1237 T/C genotypes or alleles. Regarding the TLR2 -196 to -174 del polymorphism, the del/del genotype and the del allele were overrepresented in the PD group compared to controls, however, this result did not reach statistical significance (P = 0.087). Further studies investigating the TLR-inflammatory background of PD are awaited to provide important insight into the aetiology of the disease.

Lack of association between CX3CR1 V249I and T280M polymorphisms and risk of Parkinson's disease in a Greek population.

Mechanisms that mediate inflammatory responses may be crucial in Parkinson's disease (PD) pathogenesis. In the brain, the chemokine receptor CX3CR1 is exclusively expressed in microglia, selectively mediating microglia-neuron interaction in response to its ligand, the chemokine fractalkine. Two functional single nucleotide polymorphisms, V249I and T280M, in the coding sequence of the CX3CR1 receptor have been found to alter ligand-receptor affinity. The aim of this study was to investigate the genetic role of CX3CR1 in sporadic PD. We examined the V249I and T280M CX3CR1 polymorphisms in a case-control study of 176 sporadic PD patients and 115 controls. Polymerase chain reaction-restriction fragment length polymorphism analysis was performed for the detection of the studied CX3CR1 genotypes. This is the first study that tests CX3CR1 gene polymorphisms in patients with PD. We found no differences in genotype or haplotype frequencies between PD patients and controls, suggesting that CX3CR1 V249I and T280M polymorphisms do not increase susceptibility to PD. Additional studies should further investigate the CX3CL1-CX3CR1 axis in PD.