Automatic quantification of REM sleep without atonia reliably identifies patients with REM sleep behavior disorder: a possible screening tool?

BACKGROUND: REM Sleep Behavior Disorder (RBD) is characterized by absence of physiological muscle atonia during REM sleep (REM sleep without atonia, RWA). Nigro-striatal dopaminergic impairment is a feature of Parkinson disease (PD) and can be identified in prodromal stages as well, such as idiopathic RBD (iRBD). Aims of this study are to explore the efficacy of an automatic RWA quantification in identifying RBD patients and the correlation between RWA and nigro-striatal dopaminergic function. METHODS: Forty-five iRBD, 46 PD with RBD, 24 PD without RBD patients and 11 healthy controls were enrolled in the Genoa Center (group A) and 25 patients with iRBD (group B) were enrolled in the Danish Center. Group A underwent brain [123I]FP-CIT-SPECT and group B underwent brain [18F]PE2I-PET as measures of nigro-striatal dopaminergic function. Chin muscle activity was recorded in all subjects and analyzed by applying a published automatic algorithm. Correlations between RWA and nigro-striatal dopaminergic function were explored. RESULTS: The automatic quantification of RWA significantly differentiated RBD from non-RBD subjects (AUC = 0.86), although with lower accuracy compared with conventional visual scoring (AUC = 0.99). No significant correlation was found between RWA and nigro-striatal dopaminergic function. CONCLUSION: The automatic quantification of RWA is a reliable tool to identify subjects with RBD and may be used as a first-line screening tool, but without correlations with nigro-striatal dopaminergic functioning.

Dog-assisted physiotherapy in amyotrophic lateral sclerosis: a randomized controlled pilot study.

BACKGROUND: Animal-assisted therapy (AAT) is an intervention in which the animal acts as a co-therapist. It has been mainly used in the context of patients with dementia, showing positive effects on psychological symptoms, but its potential as a physiotherapy treatment for patients with neuromuscular disorders, amyotrophic lateral sclerosis (ALS) in particular, has not yet been investigated. AIM: The aim of the study was to evaluate the impact of AAT, specifically of dog-assisted therapy, on motor functions and psychological status in patients with ALS. DESIGN: This study was a randomized controlled pilot study. SETTING: The study was carried out at the Rehabilitation Unit NEuroMuscular Omnicenter (NEMO) of Arenzano, Genoa. POPULATION: Sixty hospitalized ALS patients were enrolled. METHODS: All patients ran a regular two-weeks neurorehabilitation program twice a day. For three days a week, in place of the morning traditional treatment, the AAT group performed a rehabilitation session with a simultaneous interaction with the therapy-dog, while the control group performed a traditional rehabilitation session. The outcome measures were the Timed Up and Go Test, the Short Physical Performance Battery (SPPB), the Six Minutes Walk Test, the Ten Meters walking Test and the Hospital Anxiety and Depression Scale. RESULTS: Both groups showed an amelioration in motor scales. However, SPPB subscales as well as HADS scores showed a statistically significant improvement only in the AAT group (P values from <0.0001 to 0.0004). Additionally, across almost all motor and psychological measures, post-treatments values were significantly better for the AAT group (P values from <0.0001 to 0.01). CONCLUSIONS: The obtained results not only suggest that AAT is comparable to traditional physiotherapy treatments, but also evidence that this type of treatment has greater beneficial effects on motor and psychological symptoms in patients with ALS. CLINICAL REHABILITATION IMPACT: This study provides first evidence that AAT is a powerful rehabilitation strategy in patients with ALS, improving both motor and psychological symptoms, and therefore possibly ameliorating quality of life.

Clinical validity of the Italian adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB) in Mild Cognitive Impairment and Alzheimer's Disease.

BACKGROUND: The identification and staging of Alzheimer's Disease (AD) represent a challenge, especially in the prodromal stage of Mild Cognitive Impairment (MCI), when cognitive changes can be subtle. Worldwide efforts were dedicated to select and harmonize available neuropsychological instruments. In Italy, the Italian Network of Neuroscience and Neuro-Rehabilitation has promoted the adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB), collecting normative data from 433 healthy controls (HC). Here, we aimed to explore the ability of I-UDSNB to differentiate between a) MCI and HC, b) AD and HC, c) MCI and AD. METHODS: One hundred thirty-seven patients (65 MCI, 72 AD) diagnosed after clinical-neuropsychological assessment, and 137 HC were included. We compared the I-UDSNB scores between a) MCI and HC, b) AD and HC, c) MCI and AD, with t-tests. To identify the test(s) most capable of differentiating between groups, significant scores were entered in binary logistic and in stepwise regressions, and then in Receiver Operating Characteristic curve analyses. RESULTS: Two episodic memory tests (Craft Story and Five Words test) differentiated MCI from HC subjects; Five Words test, Semantic Fluency (vegetables), and TMT-part B differentiated AD from, respectively, HC and MCI. CONCLUSIONS: Our findings indicate that the I-UDSNB is a suitable tool for the harmonized and concise assessment of patients with cognitive decline, showing high sensitivity and specificity for the diagnosis of MCI and AD.

Selective Alteration of the Left Arcuate Fasciculus in Two Patients Affected by Creatine Transporter Deficiency.

(1) Background: In hereditary creatine transporter deficiency (CTD), there is an absence of creatine in the brain and neurological symptoms are present, including severe language impairment. However, the pathological changes caused by creatine deficiency that generate neuropsychological symptoms have been poorly studied. (2) Aims: To investigate if the language impairment in CTD is underpinned by possible pathological changes. (3) Methods: We used MRI tractography to investigate the trophism of the left arcuate fasciculus, a white matter bundle connecting Wernicke's and Broca's language areas that is specifically relevant for language establishment and maintenance, in two patients (28 and 18 y.o.). (4) Results: The T1 and T2 MRI imaging results were unremarkable, but the left arcuate fasciculus showed a marked decrease in mean fractional anisotropy (FA) compared to healthy controls. In contrast, the FA values in the corticospinal tract were similar to those of healthy controls. Although white matter atrophy has been reported in CTD, this is the first report to show a selective abnormality of the language-relevant arcuate fasciculus, suggesting a possible region-specific impact of creatine deficiency.

Cognitive impairment assessment through handwriting (COGITAT) score: a novel tool that predicts cognitive state from handwriting for forensic and clinical applications.

Introduction: Handwriting deteriorates proportionally to the writer's cognitive state. Such knowledge is of special importance in the case of a contested will, where dementia of the testator is claimed, but medical records are often insufficient to decide what the testator's cognitive state really was. By contrast, if the will is handwritten, handwriting analysis allows us to gauge the testator's cognitive state at the precise moment when he/she was writing the will. However, quantitative methods are needed to precisely evaluate whether the writer's cognitive state was normal or not. We aim to provide a test that quantifies handwriting deterioration to gauge a writer's cognitive state. Methods: We consecutively enrolled patients who came for the evaluation of cognitive impairment at the Outpatient Clinic for Cognitive Impairment of the Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Sciences (DINOGMI) of the University of Genoa, Italy. Additionally, we enrolled their caregivers. We asked them to write a short text by hand, and we administered the Mini Mental State Examination (MMSE). Then, we investigated which handwriting parameters correlated with cognitive state as gauged by the MMSE. Results: Our study found that a single score, which we called the COGnitive Impairment Through hAndwriTing (COGITAT) score, reliably allows us to predict the writer's cognitive state. Conclusion: The COGITAT score may be a valuable tool to gage the cognitive state of the author of a manuscript. This score may be especially useful in contested handwritten wills, where clinical examination of the writer is precluded.

Artificial intelligence of imaging and clinical neurological data for predictive, preventive and personalized (P3) medicine for Parkinson Disease: The NeuroArtP3 protocol for a multi-center research study.

BACKGROUND: The burden of Parkinson Disease (PD) represents a key public health issue and it is essential to develop innovative and cost-effective approaches to promote sustainable diagnostic and therapeutic interventions. In this perspective the adoption of a P3 (predictive, preventive and personalized) medicine approach seems to be pivotal. The NeuroArtP3 (NET-2018-12366666) is a four-year multi-site project co-funded by the Italian Ministry of Health, bringing together clinical and computational centers operating in the field of neurology, including PD. OBJECTIVE: The core objectives of the project are: i) to harmonize the collection of data across the participating centers, ii) to structure standardized disease-specific datasets and iii) to advance knowledge on disease's trajectories through machine learning analysis. METHODS: The 4-years study combines two consecutive research components: i) a multi-center retrospective observational phase; ii) a multi-center prospective observational phase. The retrospective phase aims at collecting data of the patients admitted at the participating clinical centers. Whereas the prospective phase aims at collecting the same variables of the retrospective study in newly diagnosed patients who will be enrolled at the same centers. RESULTS: The participating clinical centers are the Provincial Health Services (APSS) of Trento (Italy) as the center responsible for the PD study and the IRCCS San Martino Hospital of Genoa (Italy) as the promoter center of the NeuroartP3 project. The computational centers responsible for data analysis are the Bruno Kessler Foundation of Trento (Italy) with TrentinoSalute4.0 -Competence Center for Digital Health of the Province of Trento (Italy) and the LISCOMPlab University of Genoa (Italy). CONCLUSIONS: The work behind this observational study protocol shows how it is possible and viable to systematize data collection procedures in order to feed research and to advance the implementation of a P3 approach into the clinical practice through the use of AI models.

Presynaptic Dopaminergic Imaging Characterizes Patients with REM Sleep Behavior Disorder Due to Synucleinopathy.

OBJECTIVE: To apply a machine learning analysis to clinical and presynaptic dopaminergic imaging data of patients with rapid eye movement (REM) sleep behavior disorder (RBD) to predict the development of Parkinson disease (PD) and dementia with Lewy bodies (DLB). METHODS: In this multicenter study of the International RBD study group, 173 patients (mean age 70.5 ± 6.3 years, 70.5% males) with polysomnography-confirmed RBD who eventually phenoconverted to overt alpha-synucleinopathy (RBD due to synucleinopathy) were enrolled, and underwent baseline presynaptic dopaminergic imaging and clinical assessment, including motor, cognitive, olfaction, and constipation evaluation. For comparison, 232 RBD non-phenoconvertor patients (67.6 ± 7.1 years, 78.4% males) and 160 controls (68.2 ± 7.2 years, 53.1% males) were enrolled. Imaging and clinical features were analyzed by machine learning to determine predictors of phenoconversion. RESULTS: Machine learning analysis showed that clinical data alone poorly predicted phenoconversion. Presynaptic dopaminergic imaging significantly improved the prediction, especially in combination with clinical data, with 77% sensitivity and 85% specificity in differentiating RBD due to synucleinopathy from non phenoconverted RBD patients, and 85% sensitivity and 86% specificity in discriminating PD-converters from DLB-converters. Quantification of presynaptic dopaminergic imaging showed that an empirical z-score cutoff of -1.0 at the most affected hemisphere putamen characterized RBD due to synucleinopathy patients, while a cutoff of -1.0 at the most affected hemisphere putamen/caudate ratio characterized PD-converters. INTERPRETATION: Clinical data alone poorly predicted phenoconversion in RBD due to synucleinopathy patients. Conversely, presynaptic dopaminergic imaging allows a good prediction of forthcoming phenoconversion diagnosis. This finding may be used in designing future disease-modifying trials. ANN NEUROL 2024;95:1178-1192.

Metabolic network alterations as a supportive biomarker in dementia with Lewy bodies with preserved dopamine transmission.

PURPOSE: Metabolic network analysis of FDG-PET utilizes an index of inter-regional correlation of resting state glucose metabolism and has been proven to provide complementary information regarding the disease process in parkinsonian syndromes. The goals of this study were (i) to evaluate pattern similarities of glucose metabolism and network connectivity in dementia with Lewy bodies (DLB) subjects with subthreshold dopaminergic loss compared to advanced disease stages and to (ii) investigate metabolic network alterations of FDG-PET for discrimination of patients with early DLB from other neurodegenerative disorders (Alzheimer's disease, Parkinson's disease, multiple system atrophy) at individual patient level via principal component analysis (PCA). METHODS: FDG-PETs of subjects with probable or possible DLB (n = 22) without significant dopamine deficiency (z-score < 2 in putamen binding loss on DaT-SPECT compared to healthy controls (HC)) were scaled by global-mean, prior to volume-of-interest-based analyses of relative glucose metabolism. Single region metabolic changes and network connectivity changes were compared against HC (n = 23) and against DLB subjects with significant dopamine deficiency (n = 86). PCA was applied to test discrimination of patients with DLB from disease controls (n = 101) at individual patient level. RESULTS: Similar patterns of hypo- (parietal- and occipital cortex) and hypermetabolism (basal ganglia, limbic system, motor cortices) were observed in DLB patients with and without significant dopamine deficiency when compared to HC. Metabolic connectivity alterations correlated between DLB patients with and without significant dopamine deficiency (R2 = 0.597, p < 0.01). A PCA trained by DLB patients with dopamine deficiency and HC discriminated DLB patients without significant dopaminergic loss from other neurodegenerative parkinsonian disorders at individual patient level (area-under-the-curve (AUC): 0.912). CONCLUSION: Disease-specific patterns of altered glucose metabolism and altered metabolic networks are present in DLB subjects without significant dopaminergic loss. Metabolic network alterations in FDG-PET can act as a supporting biomarker in the subgroup of DLB patients without significant dopaminergic loss at symptoms onset.

Tracking the progression of Alzheimer's disease: Insights from metabolic patterns of SOMI stages.

BACKGROUND: SOMI (Stages of Objective Memory Impairment) is a novel classification that identifies six stages of memory decline in Alzheimer's Disease (AD) using the Free and Cued Selective Reminding Test (FCSRT). However, the relationship between SOMI stages and brain metabolism remains unexplored. This study aims to investigate the metabolic correlates of SOMI stages using FDG-PET in Mild Cognitive Impairment due to AD (MCI-AD) and early AD patients. METHODS: One hundred twenty-nine-patients (99 aMCI-AD and 30 AD), and 42 healthy controls (HCs) (MMSE = 29.2 ± .8; age:69.1 ± 8.6 years; education:10.7 ± 3.8 years) who underwent an extensive neuropsychological battery including FCSRT and brain FDG-PET were enrolled. According to their clinical relevance and available sample sizes, SOMI-4 (N = 24 subjects; MMSE score:26.6 ± 2.6: age:75.4 ± 3.2; education:9.9 ± 4.5) and SOMI-5 groups (N = 97; MMSE:25.3 ± 2.6; age:73.9 ± 5.8; education:9.4 ± 4.1) were investigated. RESULTS: Compared to HCs, SOMI-4 showed hypometabolism in the precuneus, medial temporal gyrus bilaterally, right pecuneus and angular gyrus. SOMI-5 exhibited broader hypometabolism, extending to the left posterior cingulate and medial frontal gyrus bilaterally. The conjunction analysis revealed overlapping areas in the precuneus, medial temporal gyrus bilaterally, and in the right angular gyrus and cuneus. The disjunction analysis identified SOMI-5 specific hypometabolism encompassing left inferior temporal gyrus, uncus and parahippocampal gyrus, and medial frontal gyrus bilaterally (p < .001, p-value (FWE) < .05). DISCUSSION: SOMI-4 relates to posterior hypometabolism, while SOMI-5 to more extensive hypometabolism further encompassing frontal cortices, suggesting SOMI as a biologically relevant classification system of memory decline. CONCLUSION: Memory decline staged with SOMI is associated with hypometabolism spreading in amnesic MCI-AD/AD, suggesting its usefulness as a clinical marker of increasing neurodegeneration.

Predicting disease severity in multiple sclerosis using multimodal data and machine learning.

BACKGROUND: Multiple sclerosis patients would benefit from machine learning algorithms that integrates clinical, imaging and multimodal biomarkers to define the risk of disease activity. METHODS: We have analysed a prospective multi-centric cohort of 322 MS patients and 98 healthy controls from four MS centres, collecting disability scales at baseline and 2 years later. Imaging data included brain MRI and optical coherence tomography, and omics included genotyping, cytomics and phosphoproteomic data from peripheral blood mononuclear cells. Predictors of clinical outcomes were searched using Random Forest algorithms. Assessment of the algorithm performance was conducted in an independent prospective cohort of 271 MS patients from a single centre. RESULTS: We found algorithms for predicting confirmed disability accumulation for the different scales, no evidence of disease activity (NEDA), onset of immunotherapy and the escalation from low- to high-efficacy therapy with intermediate to high-accuracy. This accuracy was achieved for most of the predictors using clinical data alone or in combination with imaging data. Still, in some cases, the addition of omics data slightly increased algorithm performance. Accuracies were comparable in both cohorts. CONCLUSION: Combining clinical, imaging and omics data with machine learning helps identify MS patients at risk of disability worsening.

Cerebrospinal fluid NPTX2 changes and relationship with regional brain metabolism metrics across mild cognitive impairment due to Alzheimer's disease.

BACKGROUND: Neuronal pentraxin-2 (NPTX2), crucial for synaptic functioning, declines in cerebrospinal fluid (CSF) as cognition deteriorates. The variations of CSF NPTX2 across mild cognitive impairment (MCI) due to Alzheimer's disease (AD) and its association with brain metabolism remain elusive, albeit relevant for patient stratification and pathophysiological insights. METHODS: We retrospectively analyzed 49 MCI-AD patients grouped by time until dementia (EMCI, n = 34 progressing within 2 years; LMCI, n = 15 progressing later/stable at follow-up). We analyzed demographic variables, cognitive status (MMSE score), and CSF NPTX2 levels using a commercial ELISA assay in EMCI, LMCI, and a control group of age-/sex-matched individuals with other non-dementing disorders (OND). Using [18F]FDG PET scans for voxel-based analysis, we explored correlations between regional brain metabolism metrics and CSF NPTX2 levels in MCI-AD patients, accounting for age. RESULTS: Baseline and follow-up MMSE scores were lower in LMCI than EMCI (p value = 0.006 and p < 0.001). EMCI exhibited significantly higher CSF NPTX2 values than both LMCI (p = 0.028) and OND (p = 0.006). We found a significant positive correlation between NPTX2 values and metabolism of bilateral precuneus in MCI-AD patients (p < 0.005 at voxel level, p < 0.05 with family-wise error correction at the cluster level). CONCLUSIONS: Higher CSF NPTX2 in EMCI compared to controls and LMCI suggests compensatory synaptic responses to initial AD pathology. Disease progression sees these mechanisms overwhelmed, lowering CSF NPTX2 approaching dementia. Positive CSF NPTX2 correlation with precuneus glucose metabolism links to AD-related metabolic changes across MCI course. These findings posit CSF NPTX2 as a promising biomarker for both AD staging and progression risk stratification.

Useful outcome measures in INPH patients evaluation.

Introduction: Idiopathic normal pressure hydrocephalus (INPH) is a neurological disorder that is potentially reversible and clinically characterized by a specific triad of symptoms, including gait disturbance, cognitive disorders, and urinary incontinence. In INPH assessment, the most commonly used test is the Timed Up and Go test (TUG), but a more comprehensive assessment would be necessary. The first aim of the present study is to verify the sensitivity of a protocol with both clinical and instrumental outcome measures for gait and balance in recognizing INPH patients. The second aim is to verify the most important spatio-temporal parameters in INPH assessment and their possible correlations with clinical outcome measures. Methods: Between January 2019 and June 2022, we evaluated 70 INPH subjects. We assessed balance performances with the Berg Balance Scale (BBS), Short Physical Performance Battery (SPPB), and TUG, both single (ST) and dual task (DT). We also performed an instrumental gait assessment with the GAITRite electronic walkway system, asking the patients to walk on the carpet for one minute at normal speed, fast speed, and while performing a dual task. We compared the results with those of 20 age-matched healthy subjects (HS). Results: INPH patients obtained statistically significant lower scores at the BBS, SPPB, and TUG DT but not at the TUG ST, likely because the DT involves cognitive factors altered in these subjects. Concerning instrumental gait evaluation, we found significant differences between HS and INPH patients in almost all spatio-temporal parameters except cadence, which is considered a relevant factor in INPH guidelines. We also found significant correlations between balance outcome measures and gait parameters. Discussion: Our results confirm the usefulness of BBS and suggest improving the assessment with SPPB. Although the TUG ST is the most commonly used test in the literature to evaluate INPH performances, it does not identify INPH; the TUG DT, instead, might be more useful. The GAITRite system is recognized as a quick and reliable tool to assess walking abilities and spatio-temporal parameters in INPH patients, and the most useful parameters are stride length, stride width, speed, and the percentage of double support. Both clinical and instrumental evaluation may be useful in recognizing subjects at risk for falls.

Clinical and dopaminergic imaging characteristics of the FARPRESTO cohort of trial-ready idiopathic rapid eye movement sleep behavior patients.

INTRODUCTION: Idiopathic/isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is considered the prodromal stage of alpha-synucleinopathies. Thus, iRBD patients are the ideal target for disease-modifying therapy. The risk FActoRs PREdictive of phenoconversion in iRBD Italian STudy (FARPRESTO) is an ongoing Italian database aimed at identifying risk factors of phenoconversion, and eventually to ease clinical trial enrollment of well-characterized subjects. METHODS: Polysomnography-confirmed iRBD patients were retrospectively and prospectively enrolled. Baseline harmonized clinical and nigrostriatal functioning data were collected at baseline. Nigrostriatal functioning was evaluated by dopamine transporter-single-photon emission computed tomography (DaT-SPECT) and categorized with visual semi-quantification. Longitudinal data were evaluated to assess phenoconversion. Cox regressions were applied to calculate hazard ratios. RESULTS: 365 patients were enrolled, and 289 patients with follow-up (age 67.7 ± 7.3 years, 237 males, mean follow-up 40 ± 37 months) were included in this study. At follow-up, 97 iRBD patients (33.6%) phenoconverted to an overt synucleinopathy. Older age, motor and cognitive impairment, constipation, urinary and sexual dysfunction, depression, and visual semi-quantification of nigrostriatal functioning predicted phenoconversion. The remaining 268 patients are in follow-up within the FARPRESTO project. CONCLUSIONS: Clinical data (older age, motor and cognitive impairment, constipation, urinary and sexual dysfunction, depression) predicted phenoconversion in this multicenter, longitudinal, observational study. A standardized visual approach for semi-quantification of DaT-SPECT is proposed as a practical risk factor for phenoconversion in iRBD patients. Of note, non-converted and newly diagnosed iRBD patients, who represent a trial-ready cohort for upcoming disease-modification trials, are currently being enrolled and followed in the FARPRESTO study. New data are expected to allow better risk characterization.

Validation of the REM behaviour disorder phenoconversion-related pattern in an independent cohort.

BACKGROUND: A brain glucose metabolism pattern related to phenoconversion in patients with idiopathic/isolated REM sleep behaviour disorder (iRBDconvRP) was recently identified. However, the validation of the iRBDconvRP in an external, independent group of iRBD patients is needed to verify the reproducibility of such pattern, so to increase its importance in clinical and research settings. The aim of this work was to validate the iRBDconvRP in an independent group of iRBD patients. METHODS: Forty iRBD patients (70 ± 5.59 years, 19 females) underwent brain [18F]FDG-PET in Seoul National University. Thirteen patients phenoconverted at follow-up (7 Parkinson disease, 5 Dementia with Lewy bodies, 1 Multiple system atrophy; follow-up time 35 ± 20.56 months) and 27 patients were still free from parkinsonism/dementia after 62 ± 29.49 months from baseline. We applied the previously identified iRBDconvRP to validate its phenoconversion prediction power. RESULTS: The iRBDconvRP significantly discriminated converters from non-converters iRBD patients (p = 0.016; Area under the Curve 0.74, Sensitivity 0.69, Specificity 0.78), and it significantly predicted phenoconversion (Hazard ratio 4.26, C.I.95%: 1.18-15.39). CONCLUSIONS: The iRBDconvRP confirmed its robustness in predicting phenoconversion in an independent group of iRBD patients, suggesting its potential role as a stratification biomarker for disease-modifying trials.

Is There a Role of Vitamin D in Alzheimer's disease?

Alzheimer's disease (AD) represents the most prevalent type of neurodegenerative dementia and the sixth leading cause of death worldwide. The so-called "non-calcemic actions" of vitamin D have been increasingly described, and its insufficiency has already been linked to the onset and progression of the main neurological diseases, including AD. Immune-mediated Aß plaque's phagocytosis and clearance, immune response, oxidative stress, and mitochondrial function are all influenced by vitamin D, and these functions are considered relevant in AD pathogenesis. However, it has been shown that the genomic vitamin D signaling pathway is already impaired in the AD brain, making things more complicated. In this paper, we aim to summarise the role of vitamin D in AD and review the results of the supplementation trials in AD patients.