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 novel variant in DYNC1H1 could contribute to human amyotrophic lateral sclerosis-frontotemporal dementia spectrum

Amyotrophic lateral sclerosis (ALS) belongs to the ALS-frontotemporal dementia (FTD) spectrum and is hallmarked by upper and lower motor neuron degeneration. Here, we present a patient with a cytoplasmic dynein 1 heavy chain 1 (DYNC1H1) pathogenic variant who fulfilled the ALS El Escorial criteria, and we review relevant literature. Using whole-exome sequencing, we identified a deleterious point variant in DYNC1H1 (c.4106A > G (p. Q1369R)) as a likely contributor to the ALS phenotype. In silico structural analysis, molecular dynamics simulation, and protein stability analysis predicted that this variant may increase DYNC1H1 protein stability. Moreover, this variant may disrupt binding of the transcription factor TFAP4, thus potentially acting as duon. Because (a) DYNC1H1 forms part of a ubiquitous eukaryotic motor protein complex, and (b) disruption of dynein function by perturbation of the dynein–dynactin protein complex is implicated in other motor neuron degenerative conditions, this variant could disrupt processes like retrograde axonal transport, neuronal migration, and protein recycling. Our findings expand the heterogenous spectrum of the DYNC1H1 pathogenic variant−associated phenotype and prompt further investigations of the role of this gene in ALS. © 2022 Mentis et al

Cognitive Impairment and Dementia in Primary Care: Current Knowledge and Future Directions Based on Findings From a Large Cross-Sectional Study in Crete, Greece

Introduction: Dementia severely affects the quality of life of patients and their caregivers; however, it is often not adequately addressed in the context of a primary care consultation, especially in patients with multi-morbidity. Study Population and Methods: A cross-sectional study was conducted between March-2013 and December-2014 among 3,140 consecutive patients aged >60 years visiting 14 primary health care practices in Crete, Greece. The Mini-Mental-State-Examination [MMSE] was used to measure cognitive status using the conventional 24-point cut-off. Participants who scored low on MMSE were matched with a group of elders scoring >24 points, according to age and education; both groups underwent comprehensive neuropsychiatric and neuropsychological assessment. For the diagnosis of dementia and Mild-Cognitive-Impairment (MCI), the Diagnostic and Statistical Manual-of-Mental-Disorders (DSM-IV) criteria and the International-Working-Group (IWG) criteria were used. Chronic conditions were categorized according to ICD-10 categories. Logistic regression was used to provide associations between chronic illnesses and cognitive impairment according to MMSE scores. Generalized Linear Model Lasso Regularization was used for feature selection in MMSE items. A two-layer artificial neural network model was used to classify participants as impaired (dementia/MCI) vs. non-impaired. Results: In the total sample of 3,140 participants (42.1% men; mean age 73.7 SD = 7.8 years), low MMSE scores were identified in 645 (20.5%) participants. Among participants with low MMSE scores 344 (54.1%) underwent comprehensive neuropsychiatric evaluation and 185 (53.8%) were diagnosed with Mild-Cognitive-Impairment (MCI) and 118 (34.3%) with dementia. Mental and behavioral disorders (F00-F99) and diseases of the nervous system (G00-G99) increased the odds of low MMSE scores in both genders. Generalized linear model lasso regularization indicated that 7/30 MMSE questions contributed the most to the classification of patients as impaired (dementia/MCI) vs. non-impaired with a combined accuracy of 82.0%. These MMSE items were questions 5, 13, 19, 20, 22, 23, and 26 of the Greek version of MMSE assessing orientation in time, repetition, calculation, registration, and visuo-constructive ability. Conclusions: Our study identified certain chronic illness-complexes that were associated with low MMSE scores within the context of primary care consultation. Also, our analysis indicated that seven MMSE items provide strong evidence for the presence of dementia or MCI. © Copyright © 2020 Bertsias, Symvoulakis, Tziraki, Panagiotakis, Mathioudakis, Zaganas, Basta, Boumpas, Simos, Vgontzas and Lionis

The Cretan Aging Cohort: Cohort Description and Burden of Dementia and Mild Cognitive Impairment

Our aim was to explore the burden of dementia in the Cretan Aging Cohort, comprised of 3140 persons aged ≥60 years (56.8% women, 5.8 ± 3.3 years formal education, 86.2% living in rural areas) who attended selected primary health-care facilities on the island of Crete, Greece. In the first study phase, a formal diagnosis of dementia had been reached in 4.0% of the participants. However, when selected 505 participants underwent thorough neuropsychiatric evaluation in the second phase of this study (344 with Mini-Mental State Examination [MMSE] <24 and 161 with MMSE ≥24), and results were extrapolated to the entire cohort, the prevalence of dementia and mild cognitive impairment was estimated at 10.8% (9.7%-11.9%) and 32.4% (30.8%-34.0%), respectively. Using both the field diagnostic data and the extrapolated data, the highest dementia prevalence (27.2%) was found in the 80- to 84-year-old group, who also showed the lowest educational level, apparently due to lack of schooling during World War II. © The Author(s) 2018

Cerebrovascular events in inflammatory bowel disease patients treated with anti-tumor necrosis factor alpha agents.

International audienceCerebro-vascular accidents (CVA) have rarely been reported in inflammatory bowel disease (IBD) patients treated with anti-tumor necrosis alpha (anti-TNFalpha) agents. Our aim here was to describe the clinical course of CVA in these patients. This was a European Crohn's and Colitis Organization (ECCO) retrospective observational study, performed as part of the CONFER project. A call to all ECCO members was made to report on IBD patients afflicted with CVA during treatment with anti-TNFalpha agents. Clinical data were recorded in a standardized CRF and analyzed for event association with anti-TNFalpha treatment. Nineteen patients were identified from 16 centers: Fourteen had Crohn's disease, four ulcerative colitis and one IBD colitis unclassified (median age at diagnosis: 38.0 years, range: 18.6-62.5). Patients received anti-TNFalpha for a median duration of 11.8 months (range: 0-62) at CVA onset and 7 had previously been treated with at least one other anti-TNFalpha agent. Complete neurological recovery was observed in 16 patients. Anti-TNFalpha was discontinued in 16/19 patients. However, recurrent CVA or neurologic deterioration was not observed in any of the 11 patients who received anti-TNFalpha after CVA (8 resumed after temporary cessation, 3 continued without interruption) for a median follow-up of 39.8 months (range: 5.6-98.2). These preliminary findings do not unequivocally indicate a causal role of anti-TNFalpha in CVA complicating IBD. Resuming or continuing anti-TNFalpha in IBD patients with CVA may be feasible and safe in selected cases, but careful weighing of IBD activity versus neurological status is prudent