Pathologic tearfulness after limbic encephalitis: A novel disorder and its neural basis

Objective We investigated the nature and neural foundations of pathologic tearfulness in a uniquely large cohort of patients who had presented with autoimmune limbic encephalitis (aLE). Methods We recruited 38 patients (26 men, 12 women; median age 63.06 years; interquartile range [IQR] 16.06 years) in the postacute phase of aLE who completed questionnaires probing emotion regulation. All patients underwent structural/functional MRI postacutely, along with 67 age- and sex-matched healthy controls (40 men, 27 women; median age 64.70 years; IQR 19.87 years). We investigated correlations of questionnaire scores with demographic, clinical, neuropsychological, and brain imaging data across patients. We also compared patients diagnosed with pathologic tearfulness and those without, along with healthy controls, on gray matter volume, resting-state functional connectivity, and activity. Results Pathologic tearfulness was reported by 50% of the patients, while no patient reported pathologic laughing. It was not associated with depression, impulsiveness, memory impairment, executive dysfunction in the postacute phase, or amygdalar abnormalities in the acute phase. It correlated with changes in specific emotional brain networks: volume reduction in the right anterior hippocampus, left fusiform gyrus, and cerebellum, abnormal hippocampal resting-state functional connectivity with the posteromedial cortex and right middle frontal gyrus, and abnormal hemodynamic activity in the left fusiform gyrus, right inferior parietal lobule, and ventral pons. Conclusions Pathologic tearfulness is common following aLE, is not a manifestation of other neuropsychiatric features, and reflects abnormalities in networks of emotion regulation beyond the acute hippocampal focus. The condition, which may also be present in other neurologic disorders, provides novel insights into the neural basis of affective control and its dysfunction in disease

Cost-effectiveness of initiating extrafine- or standard size-particle inhaled corticosteroid for asthma in two health-care systems: a retrospective matched cohort study

Data acquisition and analyses were funded by Teva Pharmaceuticals

Human Disease-Drug Network Based on Genomic Expression Profiles

BACKGROUND: Drug repositioning offers the possibility of faster development times and reduced risks in drug discovery. With the rapid development of high-throughput technologies and ever-increasing accumulation of whole genome-level datasets, an increasing number of diseases and drugs can be comprehensively characterized by the changes they induce in gene expression, protein, metabolites and phenotypes. METHODOLOGY/PRINCIPAL FINDINGS: We performed a systematic, large-scale analysis of genomic expression profiles of human diseases and drugs to create a disease-drug network. A network of 170,027 significant interactions was extracted from the approximately 24.5 million comparisons between approximately 7,000 publicly available transcriptomic profiles. The network includes 645 disease-disease, 5,008 disease-drug, and 164,374 drug-drug relationships. At least 60% of the disease-disease pairs were in the same disease area as determined by the Medical Subject Headings (MeSH) disease classification tree. The remaining can drive a molecular level nosology by discovering relationships between seemingly unrelated diseases, such as a connection between bipolar disorder and hereditary spastic paraplegia, and a connection between actinic keratosis and cancer. Among the 5,008 disease-drug links, connections with negative scores suggest new indications for existing drugs, such as the use of some antimalaria drugs for Crohn's disease, and a variety of existing drugs for Huntington's disease; while the positive scoring connections can aid in drug side effect identification, such as tamoxifen's undesired carcinogenic property. From the approximately 37K drug-drug relationships, we discover relationships that aid in target and pathway deconvolution, such as 1) KCNMA1 as a potential molecular target of lobeline, and 2) both apoptotic DNA fragmentation and G2/M DNA damage checkpoint regulation as potential pathway targets of daunorubicin. CONCLUSIONS/SIGNIFICANCE: We have automatically generated thousands of disease and drug expression profiles using GEO datasets, and constructed a large scale disease-drug network for effective and efficient drug repositioning as well as drug target/pathway identification

Genomic Characterization of Host Factors Related to SARS-CoV-2 Infection in People with Dementia and Control Populations: The GR@ACE/DEGESCO Study

Emerging studies have suggested several chromosomal regions as potential host genetic factors involved in the susceptibility to SARS-CoV-2 infection and disease outcome. We nested a COVID-19 genome-wide association study using the GR@ACE/DEGESCO study, searching for susceptibility factors associated with COVID-19 disease. To this end, we compared 221 COVID-19 confirmed cases with 17,035 individuals in whom the COVID-19 disease status was unknown. Then, we performed a meta-analysis with the publicly available data from the COVID-19 Host Genetics Initiative. Because the APOE locus has been suggested as a potential modifier of COVID-19 disease, we added sensitivity analyses stratifying by dementia status or by disease severity. We confirmed the existence of the 3p21.31 region (LZTFL1, SLC6A20) implicated in the susceptibility to SARS-CoV-2 infection and TYK2 gene might be involved in COVID-19 severity. Nevertheless, no statistically significant association was observed in the COVID-19 fatal outcome or in the stratified analyses (dementia-only and non-dementia strata) for the APOE locus not supporting its involvement in SARS-CoV-2 pathobiology or COVID-19 prognosis

Deciphering Diseases and Biological Targets for Environmental Chemicals using Toxicogenomics Networks

Exposure to environmental chemicals and drugs may have a negative effect on human health. A better understanding of the molecular mechanism of such compounds is needed to determine the risk. We present a high confidence human protein-protein association network built upon the integration of chemical toxicology and systems biology. This computational systems chemical biology model reveals uncharacterized connections between compounds and diseases, thus predicting which compounds may be risk factors for human health. Additionally, the network can be used to identify unexpected potential associations between chemicals and proteins. Examples are shown for chemicals associated with breast cancer, lung cancer and necrosis, and potential protein targets for di-ethylhexyl-phthalate, 2,3,7,8-tetrachlorodibenzo-p-dioxin, pirinixic acid and permethrine. The chemical-protein associations are supported through recent published studies, which illustrate the power of our approach that integrates toxicogenomics data with other data types

Tracing the ancestry of modern bread wheats

For more than 10,000 years, the selection of plant and animal traits that are better tailored for human use has shaped the development of civilizations. During this period, bread wheat (Triticum aestivum) emerged as one of the world’s most important crops. We use exome sequencing of a worldwide panel of almost 500 genotypes selected from across the geographical range of the wheat species complex to explore how 10,000 years of hybridization, selection, adaptation and plant breeding has shaped the genetic makeup of modern bread wheats. We observe considerable genetic variation at the genic, chromosomal and subgenomic levels, and use this information to decipher the likely origins of modern day wheats, the consequences of range expansion and the allelic variants selected since its domestication. Our data support a reconciled model of wheat evolution and provide novel avenues for future breeding improvement.</p

Genetic evaluation of dementia with Lewy bodies implicates distinct disease subgroups

The APOE locus is strongly associated with risk for developing Alzheimer's disease and dementia with Lewy bodies. In particular, the role of the APOE ϵ4 allele as a putative driver of α-synuclein pathology is a topic of intense debate. Here, we performed a comprehensive evaluation in 2466 dementia with Lewy bodies cases versus 2928 neurologically healthy, aged controls. Using an APOE-stratified genome-wide association study approach, we found that GBA is associated with risk for dementia with Lewy bodies in patients without APOE ϵ4 (P = 6.58 × 10-9, OR = 3.41, 95% CI = 2.25-5.17), but not with dementia with Lewy bodies with APOE ϵ4 (P = 0.034, OR = 1.87, 95%, 95% CI = 1.05-3.37). We then divided 495 neuropathologically examined dementia with Lewy bodies cases into three groups based on the extent of concomitant Alzheimer's disease co-pathology: Pure dementia with Lewy bodies (n = 88), dementia with Lewy bodies with intermediate Alzheimer's disease co-pathology (n = 66) and dementia with Lewy bodies with high Alzheimer's disease co-pathology (n = 341). In each group, we tested the association of the APOE ϵ4 against the 2928 neurologically healthy controls. Our examination found that APOE ϵ4 was associated with dementia with Lewy bodies + Alzheimer's disease (P = 1.29 × 10-32, OR = 4.25, 95% CI = 3.35-5.39) and dementia with Lewy bodies + intermediate Alzheimer's disease (P = 0.0011, OR = 2.31, 95% CI = 1.40-3.83), but not with pure dementia with Lewy bodies (P = 0.31, OR = 0.75, 95% CI = 0.43-1.30). In conclusion, although deep clinical data were not available for these samples, our findings do not support the notion that APOE ϵ4 is an independent driver of α-synuclein pathology in pure dementia with Lewy bodies, but rather implicate GBA as the main risk gene for the pure dementia with Lewy bodies subgroup