Personalized screening and risk profiles for Mild Cognitive Impairment via a Machine Learning Framework: Implications for general practice.

peer reviewedOBJECTIVES: Diagnosis of Mild Cognitive Impairment (MCI) requires lengthy diagnostic procedures, typically available at tertiary Health Care Centers (HCC). This prospective study evaluated a flexible Machine Learning (ML) framework toward identifying persons with MCI or dementia based on information that can be readily available in a primary HC setting. METHODS: Demographic and clinical data, informant ratings of recent behavioral changes, self-reported anxiety and depression symptoms, subjective cognitive complaints, and Mini Mental State Examination (MMSE) scores were pooled from two aging cohorts from the island of Crete, Greece (N = 763 aged 60-93 years) comprising persons diagnosed with MCI (n = 277) or dementia (n = 153), and cognitively non-impaired persons (CNI, n = 333). A Balanced Random Forest Classifier was used for classification and variable importance-based feature selection in nested cross-validation schemes (CNI vs MCI, CNI vs Dementia, MCI vs Dementia). Global-level model-agnostic analyses identified predictors displaying nonlinear behavior. Local level agnostic analyses pinpointed key predictor variables for a given classification result after statistically controlling for all other predictors in the model. RESULTS: Classification of MCI vs CNI was achieved with improved sensitivity (74 %) and comparable specificity (73 %) compared to MMSE alone (37.2 % and 94.3 %, respectively). Additional high-ranking features included age, education, behavioral changes, multicomorbidity and polypharmacy. Higher classification accuracy was achieved for MCI vs Dementia (sensitivity/specificity = 87 %) and CNI vs Dementia (sensitivity/specificity = 94 %) using the same set of variables. Model agnostic analyses revealed notable individual variability in the contribution of specific variables toward a given classification result. CONCLUSIONS: Improved capacity to identify elderly with MCI can be achieved by combining demographic and medical information readily available at the PHC setting with MMSE scores, and informant ratings of behavioral changes. Explainability at the patient level may help clinicians identify specific predictor variables and patient scores to a given prediction outcome toward personalized risk assessment

Environmental risk factors for dementia: a systematic review

Background - Dementia risk reduction is a major and growing public health priority. While certain modifiable risk factors for dementia have been identified, there remains a substantial proportion of unexplained risk. There is evidence that environmental risk factors may explain some of this risk. Thus, we present the first comprehensive systematic review of environmental risk factors for dementia. Methods - We searched the PubMed and Web of Science databases from their inception to January 2016, bibliographies of review articles, and articles related to publically available environmental data. Articles were included if they examined the association between an environmental risk factor and dementia. Studies with another outcome (for example, cognition), a physiological measure of the exposure, case studies, animal studies, and studies of nutrition were excluded. Data were extracted from individual studies which were, in turn, appraised for methodological quality. The strength and consistency of the overall evidence for each risk factor identified was assessed. Results - We screened 4784 studies and included 60 in the review. Risk factors were considered in six categories: air quality, toxic heavy metals, other metals, other trace elements, occupational-related exposures, and miscellaneous environmental factors. Few studies took a life course approach. There is at least moderate evidence implicating the following risk factors: air pollution; aluminium; silicon; selenium; pesticides; vitamin D deficiency; and electric and magnetic fields. Conclusions - Studies varied widely in size and quality and therefore we must be circumspect in our conclusions. Nevertheless, this extensive review suggests that future research could focus on a short list of environmental risk factors for dementia. Furthermore, further robust, longitudinal studies with repeated measures of environmental exposures are required to confirm these associations

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues

Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

Against Origen and/or Origenists? Cyril of Alexandria’s rejection of John the Baptist’s angelic nature in his Commentary on John 1:6

In his Commentary on John 1:6, Cyril of Alexandria rejects the conjecture (hyponoia) of ‘certain men’ (tines) that John the Baptist was an angel, sent by God, who took a human body. The text of Origen’s Commentary on John 1:6, which survives in Greek, enables us to identify ‘certain men’ mentioned by Cyril as Origen, and to show, for the first time, the direct access that Cyril had to that particular work of Origen. Does Cyril, however, target Origen personally with this criticism? Does he seek to condemn him in particular? No answer can be given, it seems, without taking into account the elements of Origen’s arguments used by the Bishop of Alexandria, and additionally, his reference to the many (polloi) who deny John the Baptist’s human nature

Les prologues des commentaires de Cyrille d’Alexandrie sur les Prophètes : analyse d’ensemble

This article offers a general analysis of the prologues of Cyril of Alexandria’s "Commentaries on the Twelve Prophets and on Isaiah", following the schema that J.-N. Guinot outlined for Theodoret of Cyrus. In his prologues, Cyril takes care to justify his exegetical enterprise to those who, in the 5th century, would consider it useless because of the already existing commentaries, and to define the principles which govern it, by giving priority to the historical-literal sense and by taking his distances from Origen’s allegorical method. In addition, he stresses the need to situate the Prophets in the Jewish history and to provide the historical context of their prophecy, and he identifies the main purpose of each prophecy mainly in relation to its Old Testament meaning

New Reasons to Doubt the Authenticity of the "Enarratio in Isaiam" Attributed to Basil of Caesarea

The present article seeks to problematize the "Enarratio in Isaiam"’s genesis, attribution and relation to Basil of Caesarea on the grounds of new evidence. On the one hand, a critical and philological re-examination of the Enarratio’s preface reveals a hitherto unnoticed textual agreement with Cyril of Alexandria’s "Commentary on the Gospel of Matthew", a number of repetitions and stylistic infelicities, and some discrepancies. On the other hand, a fresh analysis of the lacuna on Is 6:1-5 and especially the double exegesis of Is 6:6-8 strongly points to a then open and unfinished text and to rewriting processes of compilation literature. No doubt the authenticity issue of the Enarratio is more complex than it appears, and needs further critical study

Εὐστάθιος Βιγγόπουλος, Ἄρχων Λαμπαδάριος τῆς Μεγάλης τοῦ Χριστοῦ Ἐκκλησίας. Εἰσαγωγή – Μουσικὲς συνθέσεις

Eustathios Vingopoulos, Archon Lampadarios of the Great Church of Christ. Introduction – Musical compositions (in Greek). Athens: Eptalophos, 2012. (510 pp.

Le "De Trinitate" du Pseudo-Didyme et le culte des archanges : un élément méconnu de datation

Pseudo-Didymus’ "De Trinitate" mentions many sanctuaries of the archangels Michael and Gabriel, finely adorned, some of which were quite famous to attract people from very far in the hope of a miracle. Although this testimony was usually considered as an ancient evidence because of its purported attribution to Didymus the Blind, it does not actually reflect the state of the archangels’ cult in the fourth century. However, it proves to be an important element for the dating of the "De Trinitate" itself, since it refers to a time when the cult of the archangels was developed in the East. The documentary and literary evidence shows that the churches dedicated to them, especially to Saint Michael, significantly multiply in the sixth century, and that their cult is being established under the reign of Justinian (527-565). It is from this period that the composition of Pseudo-Didymus’ "De Trinitate" is likely to date