A CHCHD6-APP axis connects amyloid and mitochondrial pathology in Alzheimer's disease.

The mechanistic relationship between amyloid-beta precursor protein (APP) processing and mitochondrial dysfunction in Alzheimer's disease (AD) has long eluded the field. Here, we report that coiled-coil-helix-coiled-coil-helix domain containing 6 (CHCHD6), a core protein of the mammalian mitochondrial contact site and cristae organizing system, mechanistically connects these AD features through a circular feedback loop that lowers CHCHD6 and raises APP processing. In cellular and animal AD models and human AD brains, the APP intracellular domain fragment inhibits CHCHD6 transcription by binding its promoter.

Prediction and evaluation of combination pharmacotherapy using natural language processing, machine learning and patient electronic health records.

Combination pharmacotherapy targets key disease pathways in a synergistic or additive manner and has high potential in treating complex diseases. Computational methods have been developed to identifying combination pharmacotherapy by analyzing large amounts of biomedical data. Existing computational approaches are often underpowered due to their reliance on our limited understanding of disease mechanisms.

ATAD3A oligomerization promotes neuropathology and cognitive deficits in Alzheimer's disease models.

Predisposition to Alzheimer's disease (AD) may arise from lipid metabolism perturbation, however, the underlying mechanism remains elusive. Here, we identify ATPase family AAA-domain containing protein 3A (ATAD3A), a mitochondrial AAA-ATPase, as a molecular switch that links cholesterol metabolism impairment to AD phenotypes. In neuronal models of AD, the 5XFAD mouse model and post-mortem AD brains, ATAD3A is oligomerized and accumulated at the mitochondria-associated ER membranes (MAMs), where it induces cholesterol accumulation by inhibiting gene expression of CYP46A1, an enzyme governing brain cholesterol clearance.

Gut-microbiota-microglia-brain interactions in Alzheimer's disease: knowledge-based, multi-dimensional characterization.

Background: Interactions between the gut microbiota, microglia, and aging may modulate Alzheimer's disease (AD) pathogenesis but the precise nature of such interactions is not known.

Methods: We developed an integrated multi-dimensional, knowledge-driven, systems approach to identify interactions among microbial metabolites, microglia, and AD. Publicly available datasets were repurposed to create a multi-dimensional knowledge-driven pipeline consisting of an integrated network of microbial metabolite-gene-pathway-phenotype (MGPPN) consisting of 34,509 nodes (216 microbial metabolites, 22,982 genes, 1329 pathways, 9982 mouse phenotypes) and 1,032,942 edges.

Increased risk for COVID-19 breakthrough infection in fully vaccinated patients with substance use disorders in the United States between December 2020 and August 2021.

Individuals with substance use disorders (SUDs) are at increased risk for COVID-19 infection and for adverse outcomes of the infection. Though vaccines are highly effective against COVID-19, their effectiveness in individuals with SUDs might be curtailed by compromised immune status and a greater likelihood of exposures, added to the waning vaccine immunity and the new SARS-CoV-2 variants. In a population-based cohort study, we assessed the risk, time trends, outcomes and disparities of COVID-19 breakthrough infection in fully vaccinated SUD patients starting 14 days after completion of vaccination.

COVID-19 and dementia: Analyses of risk, disparity, and outcomes from electronic health records in the US.

Introduction: At present, there is limited data on the risks, disparity, and outcomes for COVID-19 in patients with dementia in the United States.

Methods: This is a retrospective case-control analysis of patient electronic health records (EHRs) of 61.9 million adult and senior patients (age ≥ 18 years) in the United States up to August 21, 2020.

COVID-19 risk, disparities and outcomes in patients with chronic liver disease in the United States.

Background: Scientific evidence is lacking regarding the risk of patients with chronic liver disease (CLD) for COVID-19, and how these risks are affected by age, gender and race.

Methods: We performed a case-control study of electronic health records of 62.2 million patients (age >18 years) in the US up to October 1st, 2020, including 1,034,270 patients with CLD, 16,530 with COVID-19, and 820 with both COVID-19 and CLD.

Drug repurposing for opioid use disorders: integration of computational prediction, clinical corroboration, and mechanism of action analyses.

Morbidity and mortality from opioid use disorders (OUD) and other substance use disorders (SUD) is a major public health crisis, yet there are few medications to treat them. There is an urgency to accelerate SUD medication development. We present an integrated drug repurposing strategy that combines computational prediction, clinical corroboration using electronic health records (EHRs) of over 72.

Analyses of Risk, Racial Disparity, and Outcomes Among US Patients With Cancer and COVID-19 Infection.

Importance: Patients with specific cancers may be at higher risk than those without cancer for coronavirus disease 2019 (COVID-19) and its severe outcomes. At present, limited data are available on the risk, racial disparity, and outcomes for COVID-19 illness in patients with cancer.

Objectives: To investigate how patients with specific types of cancer are at risk for COVID-19 infection and its adverse outcomes and whether there are cancer-specific race disparities for COVID-19 infection.

Oligodendroglial glycolytic stress triggers inflammasome activation and neuropathology in Alzheimer's disease.

Myelin degeneration and white matter loss resulting from oligodendrocyte (OL) death are early events in Alzheimer's disease (AD) that lead to cognitive deficits; however, the underlying mechanism remains unknown. Here, we find that mature OLs in both AD patients and an AD mouse model undergo NLR family pyrin domain containing 3 (NLRP3)-dependent Gasdermin D-associated inflammatory injury, concomitant with demyelination and axonal degeneration. The mature OL-specific knockdown of dynamin-related protein 1 (Drp1; a mitochondrial fission guanosine triphosphatase) abolishes NLRP3 inflammasome activation, corrects myelin loss, and improves cognitive ability in AD mice.

When hematologic malignancies meet COVID-19 in the United States: Infections, death and disparities.

Scientific data is limited on the risks, adverse outcomes and racial disparities for COVID-19 illness in individuals with hematologic malignancies in the United States. To fill this void, we screened and analyzed a nation-wide database of patient electronic health records (EHRs) of 73 million patients in the US (up to September 1st) for COVID-19 and eight major types of hematologic malignancies. Patients with hematologic malignancies had increased odds of COVID-19 infection compared with patients without hematologic malignancies for both all-time diagnosis (malignancy diagnosed in the past year or prior) (adjusted Odds ratio or AOR: 2.

Increased risk of COVID-19 infection and mortality in people with mental disorders: analysis from electronic health records in the United States.

Concerns have been expressed that persons with a pre-existing mental disorder may represent a population at increased risk for COVID-19 infec-tion and with a higher likelihood of adverse outcomes of the infection, but there is no systematic research evidence in this respect. This study assessed the impact of a recent (within past year) diagnosis of a mental disorder - including attention-deficit/hyperactivity disorder (ADHD), bipolar disorder, depression and schizophrenia - on the risk for COVID-19 infection and related mortality and hospitalization rates. We analyzed a nation-wide database of electronic health records of 61 million adult patients from 360 hospitals and 317,000 providers, across 50 states in the US, up to July 29, 2020.

CoMNRank: An integrated approach to extract and prioritize human microbial metabolites from MEDLINE records.

Motivation: Trillions of bacteria in human body (human microbiota) affect human health and diseases by controlling host functions through small molecule metabolites.An accurate and comprehensive catalog of the metabolic output from human microbiota is critical for our deep understanding of how microbial metabolism contributes to human health.The large number of published biomedical research articles is a rich resource of microbiome studies.

Automatic extraction, prioritization and analysis of gut microbial metabolites from biomedical literature.

Many diseases are driven by gene-environment interactions. One important environmental factor is the metabolic output of human gut microbiota. A comprehensive catalog of human metabolites originated in microbes is critical for data-driven approaches to understand how microbial metabolism contributes to human health and diseases.

Immunotherapy-related adverse events (irAEs): extraction from FDA drug labels and comparative analysis.

Objectives: Immune checkpoint inhibitors (ICIs) have dramatically improved outcomes in cancer patients. However, ICIs are associated with significant immune-related adverse events (irAEs) and the underlying biological mechanisms are not well-understood. To ensure safe cancer treatment, research efforts are needed to comprehensively detect and understand irAEs.

Disease comorbidity-guided drug repositioning: a case study in schizophrenia.

Unlabelled: The key to any computational drug repositioning is the availability of relevant data in machine-understandable format. While large amount of genetic, genomic and chemical data are publicly available, large-scale higher-level disease and drug phenotypic data are limited. We recently constructed a large-scale disease-comorbidity relationship knowledge base (dCombKB) and a comprehensive drug-treatment relationship knowledge base (TreatKB) from 21 million biomedical research articles and other resources.

Data-driven multiple-level analysis of gut-microbiome-immune-joint interactions in rheumatoid arthritis.

Background: Rheumatoid arthritis (RA) is the most common autoimmune disease and affects about 1% of the population. The cause of RA remains largely unknown and could result from a complex interaction between genes and environment factors. Recent studies suggested that gut microbiota and their collective metabolic outputs exert profound effects on the host immune system and are implicated in RA.

Evaluating class III antiarrhythmic agents as novel MYC targeting drugs in ovarian cancer.

Objective: To evaluate the utility of amiodarone and its derivative dronedarone as novel drug repositioning candidates in EOC and to determine the potential pathways targeted by these drugs.

Methods: Drug-predict bioinformatics platform was used to assess the utility of amiodarone as a novel drug-repurposing candidate in EOC. EOC cells were treated with amiodarone and dronedarone.

Combining mechanism-based prediction with patient-based profiling for psoriasis metabolomics biomarker discovery.

Unlabelled: Psoriasis is a chronic, debilitating skin condition that affects approximately 125 million individuals worldwide. The cause of psoriasis appears multifactorial, and no unified mitigating signal or single antigenic target has been identified to date. Metabolomic studies hold great potential for explaining disease mechanism, facilitating early diagnosis, and identifying potential therapeutic areas.

Drug repositioning for prostate cancer: using a data-driven approach to gain new insights.

Unlabelled: Prostate cancer (PC) is the most common cancer and the third leading cause of cancer death in men worldwide. Despite its high incidence and mortality, the likelihood of a cure is low for late-stages of PC. There is an unmet need for more effective agents for treating PC.

A systems biology approach to predict and characterize human gut microbial metabolites in colorectal cancer.

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths. It is estimated that about half the cases of CRC occurring today are preventable. Recent studies showed that human gut microbiota and their collective metabolic outputs play important roles in CRC.

MetabolitePredict: A de novo human metabolomics prediction system and its applications in rheumatoid arthritis.

Unlabelled: Human metabolomics has great potential in disease mechanism understanding, early diagnosis, and therapy. Existing metabolomics studies are often based on profiling patient biofluids and tissue samples and are difficult owing to the challenges of sample collection and data processing. Here, we report an alternative approach and developed a computation-based prediction system, MetabolitePredict, for disease metabolomics biomarker prediction.