GestaltMatcher Database - A global reference for facial phenotypic variability in rare human diseases

The most important factor that complicates the work of dysmorphologists is the significant phenotypic variability of the human face. Next-Generation Phenotyping (NGP) tools that assist clinicians with recognizing characteristic syndromic patterns are particularly challenged when confronted with patients from populations different from their training data. To that end, we systematically analyzed the impact of genetic ancestry on facial dysmorphism. For that purpose, we established the GestaltMatcher Database (GMDB) as a reference dataset for medical images of patients with rare genetic disorders from around the world. We collected 10,980 frontal facial images - more than a quarter previously unpublished - from 8,346 patients, representing 581 rare disorders. Although the predominant ancestry is still European (67%), data from underrepresented populations have been increased considerably via global collaborations (19% Asian and 7% African). This includes previously unpublished reports for more than 40% of the African patients. The NGP analysis on this diverse dataset revealed characteristic performance differences depending on the composition of training and test sets corresponding to genetic relatedness. For clinical use of NGP, incorporating non-European patients resulted in a profound enhancement of GestaltMatcher performance. The top-5 accuracy rate increased by +11.29%. Importantly, this improvement in delineating the correct disorder from a facial portrait was achieved without decreasing the performance on European patients. By design, GMDB complies with the FAIR principles by rendering the curated medical data findable, accessible, interoperable, and reusable. This means GMDB can also serve as data for training and benchmarking. In summary, our study on facial dysmorphism on a global sample revealed a considerable cross ancestral phenotypic variability confounding NGP that should be counteracted by international efforts for increasing data diversity. GMDB will serve as a vital reference database for clinicians and a transparent training set for advancing NGP technology.

GestaltMatcher Database - A global reference for facial phenotypic variability in rare human diseases

The most important factor that complicates the work of dysmorphologists is the significant phenotypic variability of the human face. Next-Generation Phenotyping (NGP) tools that assist clinicians with recognizing characteristic syndromic patterns are particularly challenged when confronted with patients from populations different from their training data. To that end, we systematically analyzed the impact of genetic ancestry on facial dysmorphism. For that purpose, we established the GestaltMatcher Database (GMDB) as a reference dataset for medical images of patients with rare genetic disorders from around the world. We collected 10,980 frontal facial images - more than a quarter previously unpublished - from 8,346 patients, representing 581 rare disorders. Although the predominant ancestry is still European (67%), data from underrepresented populations have been increased considerably via global collaborations (19% Asian and 7% African). This includes previously unpublished reports for more than 40% of the African patients. The NGP analysis on this diverse dataset revealed characteristic performance differences depending on the composition of training and test sets corresponding to genetic relatedness. For clinical use of NGP, incorporating non-European patients resulted in a profound enhancement of GestaltMatcher performance. The top-5 accuracy rate increased by +11.29%. Importantly, this improvement in delineating the correct disorder from a facial portrait was achieved without decreasing the performance on European patients. By design, GMDB complies with the FAIR principles by rendering the curated medical data findable, accessible, interoperable, and reusable. This means GMDB can also serve as data for training and benchmarking. In summary, our study on facial dysmorphism on a global sample revealed a considerable cross ancestral phenotypic variability confounding NGP that should be counteracted by international efforts for increasing data diversity. GMDB will serve as a vital reference database for clinicians and a transparent training set for advancing NGP technology.

EXAMINATION OF THE INCIDENCE OF POOR SLEEP QUALITY AND FACTORS ASSOCIATED FOR POOR SLEEP DURING THE VARIOUS PHASES OF PREGNANCIES

Objective - to measure poor sleep quality, its components, and the variables that contribute to it in a cohort of pregnant women across time. Four hundred and eighty-six strong singleton pregnancies were collected ahead of the fourteenth gestational week. Data on poor sleep quality were gathered before pregnancy and analyzed five distinct times in each trimester and six months after delivery. "Poor sleep quality (PSQ) was defined as a score of fewer than eight on the Athens Insomnia Scale (AIS), and for each trimester, adjusted odds ratios (aOR) with 95% confidence intervals (CI)"were acquired by use of multivariate logistic regression analysis. Pregnancy prevalence of poor SQ was 6.1 percent, followed by 44.2 percent in the first trimester (TR1), 46.3 percent in the second trimester (TR2), and 63.7 percent in the third trimester (TR3). Poor sleep quality after pregnancy was reported by 33.2 percent of women "(28.2-37.9) (p<0.001 for pre-gestational versus TR1, TR2 vs. TR3, and TR3 vs. post-pregnancy)."Due to a decrease in the quality of their nocturnal sleep, TR3's mean AIS score went from 2.34 before pregnant to 9.87; in contrast, TR1's detrimental impact on daytime functioning was larger. Poor sleep during the previous trimester was linked to poor sleep in TR2 and TR3. Poor SQ during pregnancy was a factor in TR1's poor SQ, and obesity was linked to bad sleep in TR3. The risks of having poor sleep quality in TR3 were instead decreased by moderate physical activity. Poor sleep throughout pregnancy was shown to be much more common than good sleep at any point in the pregnancy. In the latter stages of pregnancy, two out of every three expecting moms suffer poor SQ. Particular attention should be paid to pre-gestational poor SQ prevention and high body mass index.

Mitochondrial dysfunction in neurodegenerative disorders

Recent advances in understanding the role of mitochondrial dysfunction in neurodegenerative diseases have expanded the opportunities for neurotherapeutics targeting mitochondria to alleviate symptoms and slow disease progression. In this review, we offer a historical account of advances in mitochondrial biology and neurodegenerative disease. Additionally, we summarize current knowledge of the normal physiology of mitochondria and the pathogenesis of mitochondrial dysfunction, the role of mitochondrial dysfunction in neurodegenerative disease, current therapeutics and recent therapeutic advances, as well as future directions for neurotherapeutics targeting mitochondrial function. A focus is placed on reactive oxygen species and their role in the disruption of telomeres and their effects on the epigenome. The effects of mitochondrial dysfunction in the etiology and progression of Alzheimer's disease, amyotrophic lateral sclerosis, Parkinson's disease, and Huntington's disease are discussed in depth. Current clinical trials for mitochondria-targeting neurotherapeutics are discussed.

Expanding the genetic causes of small-fiber neuropathy: SCN genes and beyond

Small-fiber neuropathy (SFN) is a disorder that exclusively affects the small nerve fibers, sparing the large nerve fibers. Thinly myelinated Aδ-fibers and unmyelinated C-fibers are damaged, leading to development of neuropathic pain, thermal dysfunction, sensory symptoms, and autonomic disturbances. Although many SFNs are secondary and due to immunological causes or metabolic disturbances, the etiology is unknown in up to half of the patients. Over the years, this proportion of "idiopathic SFN" has decreased, as familial and genetic causes have been discovered, thus shifting a proportion of once "idiopathic" cases to the genetic category. After the discovery of SCN9A-gene variants in 2012, SCN10A and SCN11A variants have been found to be pathogenic in SFN. With improved accessibility of SFN diagnostic tools and genetic tests, many non-SCN variants and genetically inherited systemic diseases involving the small nerve fibers have also been described, but only scattered throughout the literature. There are 80 SCN variants described as causing SFN, 8 genes causing hereditary sensory autonomic neuropathies (HSAN) described with pure SFN, and at least 7 genes involved in genetically inherited systemic diseases associated with SFN. This systematic review aims to consolidate and provide an updated overview on the genetic variants of SFN to date---SCN genes and beyond. Awareness of these genetic causes of SFN is imperative for providing treatment directions, prognostication, and management of expectations for patients and their health-care providers.

Co-occurrence of VHL and SDHA Pathogenic Variants: A Case Report

Von Hippel Lindau(VHL)syndrome presents with cerebellar and spinal hemangioblastomas, renal cell cancer, neuroendocrine pancreatic tumor, and pheochromocytoma and it is caused by germline mutations in the VHL gene. Pathogenic germline variants in the succinate dehydrogenase A (SDHA) gene are associated with paraganglioma and pheochromocytoma. Here we report co-occurrence of germline pathogenic variants in both VHL and SDHA genes in a patient who presented with pancreatic neuroendocrine tumor. As these genes converge on the pseudo-hypoxia signaling pathway, further studies are warranted to determine the significance of co-occurrence of these variants in relation to tumor penetrance, disease severity, treatment response and clinical outcomes in this selected group of patients.

Retinal ciliopathies through the lens of Bardet-Biedl Syndrome: Past, present and future

The primary cilium is a highly specialized and evolutionary conserved organelle in eukaryotes that plays a significant role in cell signaling and trafficking. Over the past few decades tremendous progress has been made in understanding the physiology of cilia and the underlying pathomechanisms of various ciliopathies. Syndromic ciliopathies consist of a group of disorders caused by ciliary dysfunction or abnormal ciliogenesis. These disorders have multiorgan involvement in addition to retinal degeneration underscoring the ubiquitous distribution of primary cilia in different cell types. Genotype-phenotype correlation is often challenging due to the allelic heterogeneity and pleiotropy of these disorders. In this review, we discuss the clinical and genetic features of syndromic ciliopathies with a focus on Bardet-Biedl syndrome (BBS) as a representative disorder. We discuss the structure and function of primary cilia and their role in retinal photoreceptors. We describe the progress made thus far in understanding the functional and genetic characterization including expression quantitative trait locus (eQTL) analysis of BBS genes. In the future directions section, we discuss the emerging technologies, such as gene therapy, as well as anticipated challenges and their implications in therapeutic development for ciliopathies.

Novel Autoantibodies in Idiopathic Small Fiber Neuropathy

Objective

Small fiber neuropathy (SFN) is clinically and etiologically heterogeneous. Although autoimmunity has been postulated to be pathophysiologically important in SFN, few autoantibodies have been described. We aimed to identify autoantibodies associated with idiopathic SFN (iSFN) by a novel high‐throughput protein microarray platform that captures autoantibodies expressed in the native conformational state.

Methods

Sera from 58 SFN patients and 20 age‐ and gender‐matched healthy controls (HCs) were screened against >1,600 immune‐related antigens. Fluorescent unit readout and postassay imaging were performed, followed by composite data normalization and protein fold change (pFC) analysis. Analysis of an independent validation cohort of 33 SFN patients against the same 20 HCs was conducted to identify reproducible proteins in both cohorts.

Results

Nine autoantibodies were screened with statistical significance and pFC criteria in both cohorts, with at least 50% change in serum levels. Three proteins showed consistently high fold changes in main and validation cohorts: MX1 (FC = 2.99 and 3.07, respectively, p = 0.003, q = 0.076), DBNL (FC = 2.11 and 2.16, respectively, p = 0.009, q < 0.003), and KRT8 (FC = 1.65 and 1.70, respectively, p = 0.043, q < 0.003). Further subgroup analysis into iSFN and SFN by secondary causes (secondary SFN) in the main cohort showed that MX1 is higher in iSFN compared to secondary SFN (FC = 1.61 vs 0.106, p = 0.009).

Interpretation

Novel autoantibodies MX1, DBNL, and KRT8 are found in iSFN. MX1 may allow diagnostic subtyping of iSFN patients. ANN NEUROL 2022;91:66–77

Anti-phospholipid syndrome and COVID-19 thrombosis: connecting the dots

As the coronavirus disease 2019 (COVID-19) pandemic, which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is spreading rapidly worldwide, it has emerged as a leading cause of mortality, resulting in >1 million deaths over the past 10 months. The pathophysiology of COVID-19 remains unclear, posing a great challenge to the medical management of patients. Recent studies have reported an unusually high prevalence of thromboembolic events in COVID-19 patients, although the mechanism remains elusive. Several studies have reported the presence of aPLs in COVID-19 patients. We have noticed similarities between COVID-19 and APS, which is an autoimmune prothrombotic disease that is often associated with an infective aetiology. Molecular mimicry and endothelial dysfunction could plausibly explain the mechanism of thrombogenesis in acquired APS. In this review, we discuss the clinicopathological similarities between COVID-19 and APS, and the potential role of therapeutic targets based on the anti-phospholipid model for COVID-19 disease.

A multinational, multicentre study on the psychological outcomes and associated physical symptoms amongst healthcare workers during COVID-19 outbreak

OBJECTIVE

Since the declaration of the coronavirus 2019 (COVID-19) outbreak as pandemic, there are reports on the increased prevalence of physical symptoms observed in the general population. We investigated the association between psychological outcomes and physical symptoms among healthcare workers.

METHODS

Healthcare workers from 5 major hospitals, involved in the care for COVID-19 patients, in Singapore and India were invited to participate in a study by performing a self-administered questionnaire within the period of February 19 to April 17, 2020. Healthcare workers included doctors, nurses, allied healthcare workers, administrators, clerical staff and maintenance workers. This questionnaire collected information on demographics, medical history, symptom prevalence in the past month, Depression Anxiety Stress Scales (DASS-21) and the Impact of Events Scale-Revised (IES-R) instrument. The prevalence of physical symptoms displayed by healthcare workers and the associations between physical symptoms and psychological outcomes of depression, anxiety, stress, and post-traumatic stress disorder (PTSD) were evaluated.

RESULTS

Out of the 906 healthcare workers who participated in the survey, 48 (5.3%) screened positive for moderate to very-severe depression, 79 (8.7%) for moderate to extremely-severe anxiety, 20 (2.2%) for moderate to extremely-severe stress, and 34 (3.8%) for moderate to severe levels of psychological distress. The commonest reported symptom was headache (32.3%), with a large number of participants (33.4%) reporting more than four symptoms. Participants who had experienced symptoms in the preceding month were more likely to be older, have pre-existing comorbidities and a positive screen for depression, anxiety, stress, and PTSD. After adjusting for age, gender and comorbidities, it was found that depression (OR 2.79, 95% CI 1.54-5.07, p = 0.001), anxiety (OR 2.18, 95% CI 1.36-3.48, p = 0.001), stress (OR 3.06, 95% CI 1.27-7.41, p = 0.13), and PTSD (OR 2.20, 95% CI 1.12-4.35, p = 0.023) remained significantly associated with the presence of physical symptoms experienced in the preceding month. Linear regression revealed that the presence of physical symptoms was associated with higher mean scores in the IES-R, DASS Anxiety, Stress and Depression subscales.

CONCLUSIONS

Our study demonstrates a significant association between the prevalence of physical symptoms and psychological outcomes among healthcare workers during the COVID-19 outbreak. We postulate that this association may be bi-directional, and that timely psychological interventions for healthcare workers with physical symptoms should be considered once an infection has been excluded.

Understanding the underlying motives and intention among Indian blood donors towards voluntary blood donation: A cross-sectional study

OBJECTIVES

The present study aims to fill the gap in the literature by conducting a comprehensive research on Indian donor's intention towards voluntary blood donation in India. The study attempts to conceptualize and validate an integrative framework incorporating voluntary function inventory (VFI) in the theory of planned behaviour (TPB) model with the purpose tomeasure the voluntary blood donation intention.

MATERIAL AND METHODS

Structural equation modeling (SEM) has been used to rigorously test the hypothesized interrelationships among the underlying motives influencing voluntary blood donation intention. A self-administered questionnaire was used to collect data from a sample of respondents selected conveniently from selct locations in India. Total 450 completed questionnaires were received out of 1000 distributed.

RESULTS

The study develops a final conceptual framework that determines the drivers of blood donor's intention towards voluntary donation. The components of theory of planned behavior (TPB) model which include 'attitude', 'subjective norms' (SN), and 'perceived behavioral control' (PBC) along with modified volunteer functions namely 'value', 'social', 'career' and 'enhancement' were found significantly explaining the donation intention in the model.

CONCLUSION

The model achieves robustness with respect to predicting Indian donor's intention towards the voluntary donation of blood. The proposed model in this study advances the theory and research on thevolunteering motives towards blood donation. The study would provide a comprehensiveunderstanding of donors' intention to the practitioners, policy makers and Non-Government Organization (NGO), helping them to frame a calibrated strategydirected towards facilitating healthy blood donation practices.

A framework of intelligent decision support system for Indian police

Purpose

– The purpose of this paper is to introduce architecture of an Intelligent Decision Support System to fulfill the emerging responsibilities of law enforcement agencies.

Design/methodology/approach

– The proposed Intelligent Police System (IPS) is designed to meet the emerging requirements and provide information at all levels of decision making by introducing a multi-level structure of user interface and crime analysis model. The proposed framework of IPS is based on data mining and performance measurement techniques to extract useful information like crime hot spots, predict crime trends and rank police administration units on the basis of crime prevention measures.

Findings

– IPS has been implemented on actual Indian crime data provided by National Crime Records Bureau (NCRB), which illustrates effectiveness and usefulness of the proposed system. IPS can play a vital role in improving outcome in the crime investigation, criminal detection and other major areas of functioning of police organization by analyzing the crime data and sharing of the information.

Research limitations/implications

– The research in intelligent police information system can be enhanced with some important additional features which include web-base management system, geographical information system, mobile adhoc network technology, etc.

Practical implications

– IPS can easily be applied to any police system in the world and can equally be useful for any law enforcement agencies for carrying out homeland security effectively.

Originality/value

– The research reported in this manuscript is outcome of the research project funded by NCRB. This paper is the first attempt to build framework of IPS for Indian police who deal with large volume and high rate of crimes that are unmatched to any police force of the world.