Immune Analysis Using Vitreous Optical Coherence Tomography Imaging in Rats with Steroid-Induced Glaucoma.

Glaucoma is a multifactorial pathology involving the immune system. The subclinical immune response plays a homeostatic role in healthy situations, but in pathological situations, it produces imbalances. Optical coherence tomography detects immune cells in the vitreous as hyperreflective opacities and these are subsequently characterised by computational analysis. This study monitors the changes in immunity in the vitreous in two steroid-induced glaucoma (SIG) animal models created with drug delivery systems (microspheres loaded with dexamethasone and dexamethasone/fibronectin), comparing both sexes and healthy controls over six months. SIG eyes tended to present greater intensity and a higher number of vitreous opacities (p < 0.05), with dynamic fluctuations in the percentage of isolated cells (10 µm2), non-activated cells (10-50 µm2), activated cells (50-250 µm2) and cell complexes (>250 µm2). Both SIG models presented an anti-inflammatory profile, with non-activated cells being the largest population in this study. However, smaller opacities (isolated cells) seemed to be the first responder to noxa since they were the most rounded (recruitment), coinciding with peak intraocular pressure increase, and showed the highest mean Intensity (intracellular machinery), even in the contralateral eye, and a major change in orientation (motility). Studying the features of hyperreflective opacities in the vitreous using OCT could be a useful biomarker of glaucoma.

Corrigendum to "Laponite for biomedical applications: An ophthalmological perspective" [Mater. Today Bio 24 (2024) 100935].

[This corrects the article DOI: 10.1016/j.mtbio.2023.100935.].

Oxidative Stress and Migraine.

The pathogenesis of migraine is not completely understood, but inflammation and oxidative stress seem to be involved, according to data from an experimental model of the disease. This narrative review summarizes data from studies on oxidative stress markers in migraine patients, case-control association studies on the possible association of candidate genes related to oxidative stress with the risk for migraine, studies showing the presence of oxidative stress in experimental models of migraine, and studies on the efficacy of antioxidant drugs in migraine therapy. Many studies have addressed the value of concentrations of prooxidant and antioxidant substances or the activity of antioxidant enzymes in different tissues (mainly in serum/plasma or in blood cells) as possible biomarkers for migraine, being thiobarbituric acid (TBA) reactive substances (TBARS) such as malonyl dialdehyde acid (MDA) and 4-hydroxynonenal, and nitric oxide (this at least during migraine attacks in patients with migraine with aura (MWA) the most reliable. In addition, the possible usefulness of antioxidant treatment is not well established, although preliminary short-term studies suggest a beneficial action of some of them such as Coenzyme Q10 and riboflavin. Both topics require further prospective, multicenter studies with a long-term follow-up period involving a large number of migraine patients and controls.

Developments in pharmacogenetics, pharmacogenomics, and personalized medicine.

The development of Pharmacogenetics and Pharmacogenomics in Western Europe is highly relevant in the worldwide scenario. Despite the usually low institutional support, many research groups, composed of basic and clinical researchers, have been actively working for decades in this field. Their contributions made an international impact and paved the way for further studies and pharmacogenomics implementation in clinical practice. In this manuscript, that makes part of the Special Issue entitled Spanish Pharmacology, we present an analysis of the state of the art of Pharmacogenetics and Pharmacogenomics research in Europe, we compare it with the developments in Spain, and we summarize the most salient contributions since 1988 to the present, as well as recent developments in the clinical application of pharmacogenomics knowledge. Finally, we present some considerations on how we could improve translation to clinical practice in this specific scenario.

Differential Study of Retinal Thicknesses in the Eyes of Alzheimer's Patients, Multiple Sclerosis Patients and Healthy Subjects.

Multiple sclerosis (MS) and Alzheimer's disease (AD) cause retinal thinning that is detectable in vivo using optical coherence tomography (OCT). To date, no papers have compared the two diseases in terms of the structural differences they produce in the retina. The purpose of this study is to analyse and compare the neuroretinal structure in MS patients, AD patients and healthy subjects using OCT. Spectral domain OCT was performed on 21 AD patients, 33 MS patients and 19 control subjects using the Posterior Pole protocol. The area under the receiver operating characteristic (AUROC) curve was used to analyse the differences between the cohorts in nine regions of the retinal nerve fibre layer (RNFL), ganglion cell layer (GCL), inner plexiform layer (IPL) and outer nuclear layer (ONL). The main differences between MS and AD are found in the ONL, in practically all the regions analysed (AUROCFOVEAL = 0.80, AUROCPARAFOVEAL = 0.85, AUROCPERIFOVEAL = 0.80, AUROC_PMB = 0.77, AUROCPARAMACULAR = 0.85, AUROCINFERO_NASAL = 0.75, AUROCINFERO_TEMPORAL = 0.83), and in the paramacular zone (AUROCPARAMACULAR = 0.75) and infero-temporal quadrant (AUROCINFERO_TEMPORAL = 0.80) of the GCL. In conclusion, our findings suggest that OCT data analysis could facilitate the differential diagnosis of MS and AD.

Detecting Structural Changes in the Choroidal Layer of the Eye in Neurodegenerative Disease Patients through Optical Coherence Tomography Image Processing.

PURPOSE: To evaluate alterations of the choroid in patients with a neurodegenerative disease versus healthy controls, a custom algorithm based on superpixel segmentation was used. DESIGN: A cross-sectional study was conducted on data obtained in a previous cohort study. SUBJECTS: Swept-source optical coherence tomography (OCT) B-scan images obtained using a Triton (Topcon, Japan) device were compiled according to current OSCAR IB and APOSTEL OCT image quality criteria. Images were included from three cohorts: multiple sclerosis (MS) patients, Parkinson disease (PD) patients, and healthy subjects. Only patients with early-stage MS and PD were included. METHODS: In total, 104 OCT B-scan images were processed using a custom superpixel segmentation (SpS) algorithm to detect boundary limits in the choroidal layer and the optical properties of the image. The algorithm groups pixels with similar structural properties to generate clusters with similar meaningful properties. MAIN OUTCOMES: SpS selects and groups the superpixels in a segmented choroidal area, computing the choroidal optical image density (COID), measured as the standard mean gray level, and the total choroidal area (CA), measured as px2. RESULTS: The CA and choroidal density (CD) were significantly reduced in the two neurodegenerative disease groups (higher in PD than in MS) versus the healthy subjects (p < 0.001); choroidal area was also significantly reduced in the MS group versus the healthy subjects. The COID increased significantly in the PD patients versus the MS patients and in the MS patients versus the healthy controls (p < 0.001). CONCLUSIONS: The SpS algorithm detected choroidal tissue boundary limits and differences optical density in MS and PD patients versus healthy controls. The application of the SpS algorithm to OCT images potentially acts as a non-invasive biomarker for the early diagnosis of MS and PD.

The OSCAR-MP Consensus Criteria for Quality Assessment of Retinal Optical Coherence Tomography Angiography.

BACKGROUND AND OBJECTIVES: Optical coherence tomography angiography (OCTA) is a noninvasive high-resolution imaging technique for assessing the retinal vasculature and is increasingly used in various ophthalmologic, neuro-ophthalmologic, and neurologic diseases. To date, there are no validated consensus criteria for quality control (QC) of OCTA. Our study aimed to develop criteria for OCTA quality assessment. METHODS: To establish criteria through (1) extensive literature review on OCTA artifacts and image quality to generate standardized and easy-to-apply OCTA QC criteria, (2) application of OCTA QC criteria to evaluate interrater agreement, (3) identification of reasons for interrater disagreement, revision of OCTA QC criteria, development of OCTA QC scoring guide and training set, and (4) validation of QC criteria in an international, interdisciplinary multicenter study. RESULTS: We identified 7 major aspects that affect OCTA quality: (O) obvious problems, (S) signal strength, (C) centration, (A) algorithm failure, (R) retinal pathology, (M) motion artifacts, and (P) projection artifacts. Seven independent raters applied the OSCAR-MP criteria to a set of 40 OCTA scans from people with MS, Sjogren syndrome, and uveitis and healthy individuals. The interrater kappa was substantial (κ 0.67). Projection artifacts were the main reason for interrater disagreement. Because artifacts can affect only parts of OCTA images, we agreed that prior definition of a specific region of interest (ROI) is crucial for subsequent OCTA quality assessment. To enhance artifact recognition and interrater agreement on reduced image quality, we designed a scoring guide and OCTA training set. Using these educational tools, 23 raters from 14 different centers reached an almost perfect agreement (κ 0.92) for the rejection of poor-quality OCTA images using the OSCAR-MP criteria. DISCUSSION: We propose a 3-step approach for standardized quality control: (1) To define a specific ROI, (2) to assess the occurrence of OCTA artifacts according to the OSCAR-MP criteria, and (3) to evaluate OCTA quality based on the occurrence of different artifacts within the ROI. OSCAR-MP OCTA QC criteria achieved high interrater agreement in an international multicenter study and is a promising QC protocol for application in the context of future clinical trials and studies.

Automatic Segmentation of Retinal Layers in Multiple Neurodegenerative Disorder Scenarios.

Retinal Optical Coherence Tomography (OCT) allows the non-invasive direct observation of the central nervous system, enabling the measurement and extraction of biomarkers from neural tissue that can be helpful in the assessment of ocular, systemic and Neurological Disorders (ND). Deep learning models can be trained to segment the retinal layers for biomarker extraction. However, the onset of ND can have an impact on the neural tissue, which can lead to the degraded performance of models not exposed to images displaying signs of disease during training. We present a fully automatic approach for the retinal layer segmentation in multiple neurodegenerative disorder scenarios, using an annotated dataset of patients of the most prevalent NDs: Alzheimer's disease, Parkinson's disease, multiple sclerosis and essential tremor, along with healthy control patients. Furthermore, we present a two-part, comprehensive study on the effects of ND on the performance of these models. The results show that images of healthy patients may not be sufficient for the robust training of automated segmentation models intended for the analysis of ND patients, and that using images representative of different NDs can increase the model performance. These results indicate that the presence or absence of patients of ND in datasets should be taken into account when training deep learning models for retinal layer segmentation, and that the proposed approach can provide a valuable tool for the robust and reliable diagnosis in multiple scenarios of ND.

Alpha-Synuclein in Peripheral Tissues as a Possible Marker for Neurological Diseases and Other Medical Conditions.

The possible usefulness of alpha-synuclein (aSyn) determinations in peripheral tissues (blood cells, salivary gland biopsies, olfactory mucosa, digestive tract, skin) and in biological fluids, except for cerebrospinal fluid (serum, plasma, saliva, feces, urine), as a marker of several diseases, has been the subject of numerous publications. This narrative review summarizes data from studies trying to determine the role of total, oligomeric, and phosphorylated aSyn determinations as a marker of various diseases, especially PD and other alpha-synucleinopathies. In summary, the results of studies addressing the determinations of aSyn in its different forms in peripheral tissues (especially in platelets, skin, and digestive tract, but also salivary glands and olfactory mucosa), in combination with other potential biomarkers, could be a useful tool to discriminate PD from controls and from other causes of parkinsonisms, including synucleinopathies.

An update on the pharmacogenetic considerations when prescribing dopamine receptor agonists for Parkinson's disease.

INTRODUCTION: Parkinson's disease is a chronic neurodegenerative multisystemic disorder that affects approximately 2% of the population over 65 years old. This disorder is characterized by motor symptoms which are frequently accompanied by non-motor symptoms such as cognitive disorders. Current drug therapies aim to reduce the symptoms and increase the patient's life expectancy. Nevertheless, there is heterogeneity in therapy response in terms of efficacy and adverse effects. This wide range in response may be linked to genetic variability. Thus, it has been suggested that pharmacogenomics may help to tailor and personalize drug therapy for Parkinson's disease. AREAS COVERED: This review describes and updates the clinical impact of genetic factors associated with the efficacy and adverse drug reactions related to common medications used to treat Parkinson's disease. Additionally, we highlight current informative recommendations for the drug treatment of Parkinson's disease. EXPERT OPINION: The pharmacokinetic, pharmacodynamic, and safety profiles of Parkinson's disease drugs do not favor the development of pharmacogenetic tests with a high probability of success. The chances of obtaining ground-breaking pharmacogenetics biomarkers for Parkinson's disease therapy are limited. Nevertheless, additional information on the metabolism of certain drugs, and an analysis of the potential of pharmacogenetics in novel drugs could be of interest.

Explainable artificial intelligence toward usable and trustworthy computer-aided diagnosis of multiple sclerosis from Optical Coherence Tomography.

BACKGROUND: Several studies indicate that the anterior visual pathway provides information about the dynamics of axonal degeneration in Multiple Sclerosis (MS). Current research in the field is focused on the quest for the most discriminative features among patients and controls and the development of machine learning models that yield computer-aided solutions widely usable in clinical practice. However, most studies are conducted with small samples and the models are used as black boxes. Clinicians should not trust machine learning decisions unless they come with comprehensive and easily understandable explanations. MATERIALS AND METHODS: A total of 216 eyes from 111 healthy controls and 100 eyes from 59 patients with relapsing-remitting MS were enrolled. The feature set was obtained from the thickness of the ganglion cell layer (GCL) and the retinal nerve fiber layer (RNFL). Measurements were acquired by the novel Posterior Pole protocol from Spectralis Optical Coherence Tomography (OCT) device. We compared two black-box methods (gradient boosting and random forests) with a glass-box method (explainable boosting machine). Explainability was studied using SHAP for the black-box methods and the scores of the glass-box method. RESULTS: The best-performing models were obtained for the GCL layer. Explainability pointed out to the temporal location of the GCL layer that is usually broken or thinning in MS and the relationship between low thickness values and high probability of MS, which is coherent with clinical knowledge. CONCLUSIONS: The insights on how to use explainability shown in this work represent a first important step toward a trustworthy computer-aided solution for the diagnosis of MS with OCT.

Vitamin D receptor and binding protein genes variants in patients with migraine.

BACKGROUND/OBJECTIVES: Several studies have shown a relationship between vitamin D and migraine, including the association between decreased serum 25-hydroxyvitamin D in patients with migraine and the positive effects of vitamin D supplementations in the therapy of this disease. Two single-nucleotide variants (SNVs) vitamin D receptor (VDR) gene, VDR rs2228570, and VDR rs731236 have shown an association with migraine risk in a previous case-control association study, while an exome sequencing study identified a rare variant in GC vitamin D binding protein gene. This study aims to look for the association between several common variants in these two genes and the risk for migraine. METHODS: We genotyped 290 patients diagnosed with migraine and 300 age-matched controls using specific TaqMan assays for VDR rs2228570, VDR rs731236, VDR rs7975232, VDR rs739837, VDR rs78783628, GC rs7041, and GC rs4588 SNVs. RESULTS: We did not find an association between these SNVs and the risk for migraine. None of these SNVs were related to the positivity of a family history of migraine or with the presence of aura. The VDR rs731236A allele showed a significant association with the triggering of migraine attacks by ethanol (Pc = 0.007). CONCLUSIONS: In summary, the results of the current study suggest a lack of association between common SNVs in the VDR and GC gene and the risk of developing migraine. The possible relationship between VDR rs731236 and the triggering of migraine episodes with ethanol deserves future studies.

Evaluation of multiple sclerosis severity using a new OCT tool.

PURPOSE: To assess the ability of a new posterior pole protocol to detect areas with significant differences in retinal nerve fiber layer (RNFL) and ganglion cell layer (GCL) thickness in patients with multiple sclerosis versus healthy control subjects; in addition, to assess the correlation between RNFL and GCL thickness, disease duration, and the Expanded Disability Status Scale (EDSS). METHODS: We analyzed 66 eyes of healthy control subjects and 100 eyes of remitting-relapsing multiple sclerosis (RR-MS) patients. Double analysis based on first clinical symptom onset (CSO) and conversion to clinically definite MS (CDMS) was performed. The RR-MS group was divided into subgroups by CSO and CDMS year: CSO-1 (≤ 5 years) and CSO-2 (≥ 6 years), and CDMS-1 (≤ 5 years) and CDMS-2 (≥ 6 years). RESULTS: Significant differences in RNFL and GCL thickness were found between the RR-MS group and the healthy controls and between the CSO and CDMS subgroups and in both layers. Moderate to strong correlations were found between RNFL and GCL thickness and CSO and CDMS. Furthermore, we observed a strong correlation with EDSS 1 year after the OCT examination. CONCLUSIONS: The posterior pole protocol is a useful tool for assessing MS and can reveal differences even in early stages of the disease. RNFL thickness shows a strong correlation with disability status, while GCL thickness correlates better with disease duration.

Sleep Disorders in Patients with Choreic Syndromes.

PURPOSE OF REVIEW: Patients with different types of choreic syndromes, specially those with Huntington's (HD) and Wilson's (WD) diseases, report frequent sleep complaints. This review focuses on the main findings of studies addressing the sleep features in these diseases, and other less frequent causes of chorea associated with sleep disorders, including a new syndrome described in the last decade associated with IgLON5 antibodies. RECENT FINDINGS: Patients with HD and WD showed a bad quality of sleep and high frequency of insomnia and excessive daytime somnolence. WD patients also showed high scores on a specific scale for rapid eye movement sleep behavior disorders. HD and WD share decreased sleep efficiency and increased REM sleep latencies, percentage of sleep stage N1, and wake after sleep onset (WASO) among their polysomnographic features. Patients with HD and WD showed a high prevalence of different sleep disorders. Patients with other causes of chorea, including neuroacanthocytosis, parasomnia with sleep breathing disorder associated with antibodies to IgLON5, Sydenham's chorea, and choreic syndromes associated to certain genetic mutations show sleep disorders as well.

The macular retinal ganglion cell layer as a biomarker for diagnosis and prognosis in multiple sclerosis: A deep learning approach.

PURPOSE: The macular ganglion cell layer (mGCL) is a strong potential biomarker of axonal degeneration in multiple sclerosis (MS). For this reason, this study aims to develop a computer-aided method to facilitate diagnosis and prognosis in MS. METHODS: This paper combines a cross-sectional study of 72 MS patients and 30 healthy control subjects for diagnosis and a 10-year longitudinal study of the same MS patients for the prediction of disability progression, during which the mGCL was measured using optical coherence tomography (OCT). Deep neural networks were used as an automatic classifier. RESULTS: For MS diagnosis, greatest accuracy (90.3%) was achieved using 17 features as inputs. The neural network architecture comprised the input layer, two hidden layers and the output layer with softmax activation. For the prediction of disability progression 8 years later, accuracy of 81.9% was achieved with a neural network comprising two hidden layers and 400 epochs. CONCLUSION: We present evidence that by applying deep learning techniques to clinical and mGCL thickness data it is possible to identify MS and predict the course of the disease. This approach potentially constitutes a non-invasive, low-cost, easy-to-implement and effective method.

Diagnosis of multiple sclerosis using optical coherence tomography supported by artificial intelligence.

BACKGROUND: Current procedures for diagnosing multiple sclerosis (MS) present a series of limitations, making it critically important to identify new biomarkers. The aim of the study was to identify new biomarkers for the early diagnosis of MS using spectral-domain optical coherence tomography (OCT) and artificial intelligence. METHODS: Spectral domain OCT was performed on 79 patients with relapsing-remitting multiple sclerosis (RRMS) (disease duration ≤ 2 years, no history of optic neuritis) and on 69 age-matched healthy controls using the posterior pole protocol that incorporates the anatomic Positioning System. Median retinal thickness values in both eyes and inter-eye difference in healthy controls and patients were evaluated by area under the receiver operating characteristic (AUROC) curve analysis in the foveal, parafoveal and perifoveal areas and in the overall area spanned by the three rings. The structures with the greatest discriminant capacity - retinal thickness and inter-eye difference - were used as inputs to a convolutional neural network to assess the diagnostic capability. RESULTS: Analysis of retinal thickness and inter-eye difference in RRMS patients revealed that greatest alteration occurred in the ganglion cell (GCL), inner plexiform (IPL), and inner retinal (IRL) layers. By using the average thickness of the GCL (AUROC = 0.82) and the inter-eye difference in the IPL (AUROC = 0.71) as inputs to a two-layer convolutional neural network, automatic diagnosis attained accuracy = 0.87, sensitivity = 0.82, and specificity = 0.92. CONCLUSION: This study adds weight to the argument that neuroretinal structure analysis could be incorporated into the diagnostic criteria for MS.