medRxiv : the preprint server for health sciences最新文献

The COVID-19 pandemic has caused substantial worldwide disruptions in health, economy, and society, manifesting symptoms such as loss of smell (anosmia) and loss of taste (ageusia), that can result in prolonged sensory impairment. Establishing the host genetic etiology of anosmia and ageusia in COVID-19 will aid in the overall understanding of the sensorineural aspect of the disease and contribute to possible treatments or cures. By using human genome sequencing data from the University of Iowa (UI) COVID-19 cohort (N=187) and the National Institute of Health All of Us (AoU) Research Program COVID-19 cohort (N=947), we investigated the genetics of anosmia and/or ageusia by employing feature selection techniques to construct a novel variant and gene prioritization pipeline, utilizing machine learning methods for the classification of patients. Models were assessed using a permutation-based variable importance (PVI) strategy for final prioritization of candidate variants and genes. The highest held-out test set area under the receiver operating characteristic (AUROC) curve for models and datasets from the UI cohort was 0.735 and 0.798 for the variant and gene analysis respectively and for the AoU cohort was 0.687 for the variant analysis. Our analysis prioritized several novel and known candidate host genetic factors involved in immune response, neuronal signaling, and calcium signaling supporting previously proposed hypotheses for anosmia/ageusia in COVID-19.

Multiple Sclerosis (MS) is a chronic inflammatory and neurodegenerative disease affecting the brain and spinal cord. Genetic studies have identified many risk loci, that were thought to primarily impact immune cells and microglia. Here, we performed a multi-ancestry genome-wide association study with 20,831 MS and 729,220 control participants, identifying 236 susceptibility variants outside the Major Histocompatibility Complex, including four novel loci. We derived a polygenic score for MS and, optimized for European ancestry, it is informative for African-American and Latino participants. Integrating single-cell data from blood and brain tissue, we identified 76 genes affected by MS risk variants. Notably, while T cells showed the strongest enrichment, inhibitory neurons emerged as a key cell type, highlighting the importance of neuronal and glial dysfunction in MS susceptibility.

Background and objective: Alzheimer's disease and related dementias (ADRDs) are progressive conditions that substantially impact individuals and families. Timely diagnosis and early support are critical for long-term adjustment. However, current dementia care models do not meet needs of patients and families. Dementia care specialists treating individuals with dementia offer unique insight into care needs of diverse groups of patients, families, and healthcare systems that can be used to identify opportunities to improve care.To understand dementia care specialists' impressions of factors impacting ADRD diagnosis and post-diagnosis support. We aimed to identify factors that impact: (1) timely and accurate diagnosis, (2) diagnostic disclosure and provision of post-diagnosis support, and (3) patient and care-partner adjustment after diagnosis.

Research design and methods: We recruited dementia care specialists treating persons living with dementia (n=19) from two academic medical centers. Participants completed 60-minute qualitative focus groups or individual interviews. Data were analyzed using a hybrid inductive-deductive approach to thematic analysis.

Results: We identified subthemes within three overarching a-priori determined themes. Participants highlighted the presence of delays in referrals, time constraints, specialist discomfort, and lack of training as factors impacting the timeliness and accuracy of diagnosis. They also highlighted information needed in disclosure visits, ways of coordinating care, and identifying early support needs. Finally, participants highlighted factors impacting adjustment including families' insight and acceptance, distress, and available resources.

Discussion and implications: Our study highlights the challenges dementia care specialist specialists face in delivering early support for individuals and families impacted by ADRDs and suggests avenues for revising existing care models.

Pervasive genetic overlap across human complex traits necessitates developing multivariate methods that can parse pleiotropic and trait-specific genetic signals. Here, we introduce Genomic Network Analysis (GNA), an analytic framework that applies the principles of network modelling to estimates of genetic overlap derived from genome-wide association study (GWAS) summary statistics. The result is a genomic network that describes the conditionally independent genetic associations between traits that remain when controlling for shared signal with the broader network of traits. Graph theory metrics provide added insight by formally quantifying the most important traits in the genomic network. GNA can discover additional trait-specific pathways by incorporating gene expression or genetic variants into the network to estimate their conditional associations with each trait. Extensive simulations establish GNA is well-powered for most GWAS. Application to a diverse set of traits demonstrate that GNA yields critical insight into the genetic architecture that demarcate genetically overlapping traits at varying levels of biological granularity.

Importance: Poor oral health, including periodontal disease, is associated with oral microbiome changes and increased mortality risk. However, no large studies have evaluated whether the oral microbiome is directly associated with mortality.

Objective: To evaluate whether measures of the oral microbiome is prospectively associated with all-cause mortality.

Design: A cross-sectional survey with samples collected from 2009-2012 and mortality linkage to the restricted-use National Death Index (NDI) through 2019.

Setting: The National Health and Nutrition Examination Survey (NHANES) 2009-2012, a multistage probability sample of the US population.

Participants: NHANES participants 20- to 69-years-old who were eligible for linkage to the NDI and provided oral rinse specimens (N=7,721, representing approximately 194 million individuals).

Exposure: Oral microbiome ascertained by sequencing the V4 region of the 16S rRNA gene of extracted DNA from oral rinse specimens. Alpha diversity, beta diversity, and genus-level data were generated using DADA2 and QIIME.

Main outcome and measure: All-cause mortality.

Results: After an average of 8.8 years, a total of 426 participants died. Using Cox proportional hazards regression and after controlling for multiple comparisons where appropriate, continuous alpha diversity was inversely associated with all-cause mortality, but only the association for the Shannon-Weiner index was significant with full adjustment for major risk factors (hazard ratio [HR] per standard deviation [SD]=0.85; 95% confidence interval [CI]=0.74-0.98). The principal coordinate analysis (PCoA) vector 2 from the Bray-Curtis dissimilarity matrix (HR per SD=0.83; 95% CI=0.73-0.93) and PCoA1 from weighted UniFrac (HR per SD=0.86; 95% CI=0.75-0.98) were significantly associated with all-cause mortality after full adjustment. Few associations were observed at the genus-level after Bonferroni correction, but an increase in 1 SD of the relative abundance of Granulicatella and Lactobacillus were associated with a 17% (95% CI=1.11-1.24) and 11% (95% CI=1.06-1.16) increase in mortality risk, respectively. Compared to participants with no detectable Bacteroides, participants in the highest tertile of Bacteroides had decreased mortality risk (HR=0.54; 95% CI=0.40-0.74).

Conclusions and relevance: Some measures of the oral microbiome were associated with all-cause mortality in this representative population cohort. These results suggest that oral bacterial communities may be important contributors to health and disease.

Objective: Lennox-Gastaut Syndrome (LGS) is a severe, often treatment-resistant epilepsy syndrome typically diagnosed in early childhood. Many have seizures before diagnosis. Some have periods of seizure freedom before treatment resistance, i.e., a "gap." Review of these gaps may identify early candidate biomarkers of LGS and/or highlight opportunities for intervention.

Methods: We reviewed charts of children diagnosed with LGS born in 2008-2010 and diagnosed with LGS by 2014 at five academic medical centers in New York City using the RENYC (Rare Epilepsies in New York City) database. We collected dates of events of potential biomarkers by chart abstraction, including onset of slow spike-and-wave (SSW) and onset and offset of seizure freedom. Seizure-free periods ("gaps") were defined as greater than 30 days without unprovoked seizures.

Results: Thirty-three children had LGS (52% male; etiology 33% structural-acquired, 6% structural-congenital, 3% genetic-structural, 24% genetic, 33% unknown). Twenty-two (67%) had a gap before diagnosis. Eight of these twenty-two (36%) had SSW described before the gap, five (23%) during the gap, and six (27%) after the gap. A history of infantile epileptic spasms syndrome (IESS), age at seizure onset, and age of tonic seizure onset were not different between those with and without a gap. Of 20 (61%) with a history of IESS, 10 (30% of the full cohort) had not received recommended therapy (i.e., ACTH, prednisolone, or vigabatrin) as first-line treatment.

Conclusions: The appearance of SSW, even in seizure-free children, may herald the development of LGS in high-risk children. Further studies on its predictive value are warranted. Our findings also highlight use of recommended first-line therapy for infantile spasms as a potentially modifiable treatment gap in children who subsequently develop LGS.

Highly Pathogenic Avian Influenza strain H5N1 has caused a multi-state outbreak among US dairy cattle, spreading across 15 states and infecting hundreds of herds since its onset. We rapidly developed and optimized PCR-based detection assays and sequencing protocols to support H5N1 molecular surveillance. Using 214 retail milk from 20 states for methods development, we found that H5N1 concentrations by digital PCR strongly correlated with qPCR cycle threshold (Ct) values, with dPCR exhibiting greater sensitivity. We also found that metagenomic sequencing after hybrid selection was best for higher concentration samples while amplicon sequencing performs best for lower concentrations. By establishing these methods, we were able to support the creation of a statewide surveillance program to test bulk milk samples monthly from all cattle dairy farms within Massachusetts, which remain negative to date. The methods, workflow, and recommendations described here provide a framework for others aiming to conduct H5N1 surveillance efforts.

Genetic mutations that yield defective cystic fibrosis transmembrane regulator (CFTR) protein cause cystic fibrosis, a life-limiting autosomal recessive Mendelian disorder. A protective role of CFTR loss-of-function mutations in inflammatory bowel disease (IBD) has been suggested, but its evidence has been inconclusive and contradictory. Here, leveraging the largest IBD exome sequencing dataset to date, comprising 38,558 cases and 66,945 controls in the discovery stage, and 35,797 cases and 179,942 controls in the replication stage, we established a protective role of CF-risk variants against IBD based on evidence from the association test of CFTR delF508 (p-value=8.96E-11) and the gene-based burden test of CF-risk variants (p-value=3.9E-07). Furthermore, we assessed variant prioritization methods, including AlphaMissense, using clinically annotated CF-risk variants as the gold standard. Our findings highlight the critical and unmet need for effective variant prioritization in gene-based burden tests.

Background & aims: Integrated HBV DNA (iDNA) plays a critical role in HBV pathogenesis, particularly in predicting treatment response and HCC. This study aimed to use an HBV hybridization-capture next-generation sequencing (HBV-NGS) assay to detect HBV-host junction sequences (HBV-JS) in a sensitive nonbiased manner to detect and estimate the iDNA fraction in tissue biopsies and HBV genetics by liquid biopsy.

Methods: HBV DNA from plasmid monomers, HBV-HCC cell line (SNU398, Hep3B, and PLC/PRF/5), tissue biopsies of patients with serum HBV DNA <4 log IU/ml, and matched urine and plasma of HBV patients were assessed by HBV-NGS. Junction-specific qPCR (JS-qPCR) assays were developed to quantify abundant HBV-JS.

Results: We demonstrated high coverage uniformity, reproducibility across all HBV genotypes A-D, and 0.1% sensitivity for detecting iDNA by the HBV-NGS assay. The sequence and structures of iDNA molecules from SNU398 and Hep3B are reported. An iDNA estimation model was developed using six abundant HBV-JS sequences identified from tissue biopsies by HBV-NGS assay and validated using total DNA of SNU398 and Hep3B cells. Furthermore, the utility of the HBV-NGS assay for HBV genetic analysis in liquid biopsies was explored using matched plasma-urine samples from three patients with serum HBV DNA levels ranging from high to undetectable. HBV-JS was detected in all body fluids tested, regardless of viral load.

Conclusion: These findings suggest that the iDNA fraction in tissue biopsies from patients with limited or undetectable serum HBV DNA can be estimated using a robust HBV-NGS assay, and a sensitive HBV genetics liquid biopsy can be obtained. This study highlights the potential of NGS-based methods to advance HBV management.