Mapping coexisting hotspots of multidimensional food market (in)accessibility and climate vulnerability.

With the increasing likelihood of agricultural production failures under a warmer global climate, the importance of markets in providing access to nutrient-dense foods (NDFs) through trade is predicted to grow. However, regions with relatively poor access to markets and supporting infrastructures (e.g. roads and storage facilities) are potentially ill-equipped to deal with both short-term hydrometeorological hazards such as droughts and floods, and longer-term shifts in agricultural productivity. Despite the increasing focus upon markets within academic and policymaking circles, a regional-scale assessment of these potentially coexisting hotspots of vulnerability has not been conducted. We conduct a two-stage geospatial analysis integrating three publicly available datasets across the Indian states of Bihar, Chhattisgarh, Jharkhand, and Odisha. Combining the 2011 national census with the new PMGSY-GeoSadak database, we conduct nearest neighbour analysis to measure multidimensional market inaccessibility by: (i) distance from a settlement to its nearest village, town or city with a market, (ii) distance from a settlement to its nearest major road, and (iii) distance from a settlement to its subdistrict headquarters. We then correlate these measures with India's only district-wise assessment of climate vulnerability to identify hotspots of market inaccessibility and climate hazards. We find that the three market access measures are spatially autocorrelated and positively interrelated at the settlement (n = 129 555) and district (n = 107) levels, meaning that settlements located further from their nearest market tend to experience poorer road connectivity and access to the subdistrict economic hub. Approximately 18.5-million people live in districts with relatively high climate vulnerability and relatively high and multidimensional market inaccessibility. Hotspots of coexisting vulnerabilities are also disproportionately populated by 'Schedule Castes and Schedule Tribes' (SC/ST) communities. The identification of coexisting hotspots has important implications for the development of equitable and resilient markets that bolster NDF access for climate vulnerable and nutritionally insecure populations.

Multiomic profiling of transcription factor binding and function in human brain.

Transcription factors (TFs) orchestrate gene expression programs crucial for brain function, but we lack detailed information about TF binding in human brain tissue. We generated a multiomic resource (ChIP-seq, ATAC-seq, RNA-seq, DNA methylation) on bulk tissues and sorted nuclei from several postmortem brain regions, including binding maps for more than 100 TFs. We demonstrate improved measurements of TF activity, including motif recognition and gene expression modeling, upon identification and removal of high TF occupancy regions. Further, predictive TF binding models demonstrate a bias for these high-occupancy sites. Neuronal TFs SATB2 and TBR1 bind unique regions depleted for such sites and promote neuronal gene expression. Binding sites for TFs, including TBR1 and PKNOX1, are enriched for risk variants associated with neuropsychiatric disorders, predominantly in neurons. This work, titled BrainTF, is a powerful resource for future studies seeking to understand the roles of specific TFs in regulating gene expression in the human brain.

Errors in Genome Sequencing Result Disclosures: A Randomized Controlled Trial Comparing Neonatology Non-Genetics Healthcare Professionals and Genetic Counselors.

PURPOSE: We compared the rate of errors in genome sequencing (GS) result disclosures by genetic counselors (GC) and trained non-genetics healthcare professionals (NGHP) in SouthSeq, a randomized trial utilizing GS in critically ill infants. METHODS: Over 400 recorded GS result disclosures were analyzed for major and minor errors. We used Fisher's exact test to compare error rates between GCs and NGHPs and performed a qualitative content analysis to characterize error themes. RESULTS: Major errors were identified in 7.5% of disclosures by NGHPs and in no disclosures by GCs. Minor errors were identified in 32.1% of disclosures by NGHPs and in 11.4% of disclosures by GCs. While most disclosures lacked errors, NGHPs were significantly more likely to make any error than GCs for all result types (positive, negative, or uncertain). Common major error themes include omission of critical information, overstating a negative result, and overinterpreting an uncertain result. The most common minor error was failing to disclose negative secondary findings. CONCLUSION: Trained NGHPs made clinically significant errors in GS result disclosures. Characterizing common errors in result disclosure can illuminate gaps in education to inform the development of future genomics training and alternative service delivery models.

A Bayesian System to Detect and Track Outbreaks of Influenza-Like Illnesses Including Novel Diseases.

BACKGROUND: The early identification of outbreaks of both known and novel influenza-like illnesses is an important public health problem. OBJECTIVE: The design and testing of a tool that detects and tracks outbreaks of both known and novel influenza-like illness, such as the SARS-CoV-19 worldwide pandemic, accurately and early. METHODS: This paper describes the ILI Tracker algorithm that first models the daily occurrence of a set of known influenza-like illnesses in hospital emergency departments in a monitored region using findings extracted from patient care reports using natural language processing. We then show how the algorithm can be extended to detect and track the presence of an unmodeled disease which may represent a novel disease outbreak. RESULTS: We include results based on modeling the diseases influenza, respiratory syncytial virus, human metapneumovirus, and parainfluenza for five emergency departments in Allegheny County Pennsylvania from June 1, 2014 through May 31, 2015. We also include the results of detecting the outbreak of an unmodeled disease, which in retrospect was very likely an outbreak of the enterovirus EV-D68. CONCLUSIONS: The results reported in this paper provide support that ILI Tracker was able to track well the incidence of four modeled influenza-like diseases over a one-year period, relative to laboratory confirmed cases, and it was computationally efficient in doing so. The system was alsoable to detect a likely novel outbreak of the enterovirus D68 early in an outbreak that occurred in Allegheny County in 2014, as well as clinically characterize that outbreak disease accurately.

Inappropriate Ordering of Multitarget Stool DNA Tests for Colon Cancer Screening.

BACKGROUND: CRC screening is recommended for adults aged 45-75. Mt-sDNA is indicated for asymptomatic individuals between the ages of 45 and 85, but not for those with rectal bleeding, iron deficiency anemia, adenomatous polyps, previous colonoscopy within 10 years, family history of CRC, positive results from CRC screening tests within the past 6 months, or age less than 45 and greater than 85. We aimed to determine the prevalence of mt-sDNA use when not indicated and factors associated with inappropriate testing. METHODS: 7,345 patients underwent mt-sDNA testing and were randomized using EMERSE. Charts for the first 500 patients were reviewed to determine whether mt-sDNA was ordered appropriately according to the USPSTF criteria. Seven patients were excluded due to having more than one inappropriate ordering for mt-sDNA. RESULTS: Of 500 patients, 22.2% had an inappropriately ordered mt-sDNA test. The most common reason for inappropriate ordering was having a previous colonoscopy done within the past 10 years. Rates of inappropriate testing significantly varied by race and the specialty of the ordering provider, with internal medicine providers ordering the most mt-sDNA tests. Rates of inappropriate testing did not significantly vary by sex or type of insurance. DISCUSSION: Our study suggests that providers may not be familiar with guidelines for the indicated use of mtsDNA, leading to inappropriate referrals and increased costs. Patients at increased CRC risk would benefit from a more sensitive procedure such as a colonoscopy. Future studies could understand the motivation to order testing outside approved indications through provider surveys and interviews.

Probabilistic association of differentially expressed genes with cis-regulatory elements.

Differential gene expression in response to perturbations is mediated at least in part by changes in binding of transcription factors (TFs) and other proteins at specific genomic regions. Association of these cis-regulatory elements (CREs) with their target genes is a challenging task that is essential to address many biological and mechanistic questions. Many current approaches rely on chromatin conformation capture techniques or single-cell correlational methods to establish CRE-to-gene associations. These methods can be effective but have limitations, including resolution, gaps in detectable association distances, and cost. As an alternative, we have developed DegCre, a nonparametric method that evaluates correlations between measurements of perturbation-induced differential gene expression and differential regulatory signal at CREs to score possible CRE-to-gene associations. It has several unique features, including the ability to use any type of CRE activity measurement, yield probabilistic scores for CRE-to-gene pairs, and assess CRE-to-gene pairings across a wide range of sequence distances. We apply DegCre to six data sets, each using different perturbations and containing a variety of regulatory signal measurements, including chromatin openness, histone modifications, and TF occupancy. To test their efficacy, we compare DegCre associations to Hi-C loop calls and CRISPR-validated CRE-to-gene associations, establishing good performance by DegCre that is comparable or superior to competing methods. DegCre is a novel approach to the association of CREs to genes from a perturbation-differential perspective, with strengths that are complementary to existing approaches and allow for new insights into gene regulation.

Long-read genome sequencing and variant reanalysis increase diagnostic yield in neurodevelopmental disorders.

Variant detection from long-read genome sequencing (lrGS) has proven to be considerably more accurate and comprehensive than variant detection from short-read genome sequencing (srGS). However, the rate at which lrGS can increase molecular diagnostic yield for rare disease is not yet precisely characterized. We performed lrGS using Pacific Biosciences "HiFi" technology on 96 short-read-negative probands with rare disease that were suspected to be genetic. We generated hg38-aligned variants and de novo phased genome assemblies, and subsequently annotated, filtered, and curated variants using clinical standards. New disease-relevant or potentially relevant genetic findings were identified in 16/96 (16.7%) probands, eight of which (8/96, 8.33%) harbored pathogenic or likely pathogenic variants. Newly identified variants were visible in both srGS and lrGS in nine probands (~9.4%) and resulted from changes to interpretation mostly from recent gene-disease association discoveries. Seven cases included variants that were only interpretable in lrGS, including copy-number variants, an inversion, a mobile element insertion, two low-complexity repeat expansions, and a 1 bp deletion. While evidence for each of these variants is, in retrospect, visible in srGS, they were either: not called within srGS data, were represented by calls with incorrect sizes or structures, or failed quality-control and filtration. Thus, while reanalysis of older data clearly increases diagnostic yield, we find that lrGS allows for substantial additional yield (7/96, 7.3%) beyond srGS. We anticipate that as lrGS analysis improves, and as lrGS datasets grow allowing for better variant frequency annotation, the additional lrGS-only rare disease yield will grow over time.

Treatment Patterns and Survival Outcomes in Patients With Breast Cancer on Medicaid, Pre- and Post-Expansion.

BACKGROUND: The objective of this study was to evaluate the impact of Medicaid expansion on breast cancer treatment and survival among Medicaid-insured women in Ohio, accounting for the timing of enrollment in Medicaid relative to their cancer diagnosis and post-expansion heterogeneous Medicaid eligibility criteria, thus addressing important limitations in previous studies. METHODS: Using 2011-2017 Ohio Cancer Incidence Surveillance System data linked with Medicaid claims data, we identified women aged 18 to 64 years diagnosed with local-stage or regional-stage breast cancer (n=876 and n=1,957 pre-expansion and post-expansion, respectively). We accounted for women's timing of enrollment in Medicaid relative to their cancer diagnosis, and flagged women post-expansion as Affordable Care Act (ACA) versus non-ACA, based on their income eligibility threshold. Study outcomes included standard treatment based on cancer stage and receipt of lumpectomy, mastectomy, chemotherapy, radiation, hormonal treatment, and/or treatment for HER2-positive tumors; time to treatment initiation (TTI); and overall survival. We conducted multivariable robust Poisson and Cox proportional hazards regression analysis to evaluate the independent associations between Medicaid expansion and our outcomes of interest, adjusting for patient-level and area-level characteristics. RESULTS: Receipt of standard treatment increased from 52.6% pre-expansion to 61.0% post-expansion (63.0% and 59.9% post-expansion in the ACA and non-ACA groups, respectively). Adjusting for potential confounders, including timing of enrollment in Medicaid, being diagnosed in the post-expansion period was associated with a higher probability of receiving standard treatment (adjusted risk ratio, 1.14 [95% CI, 1.06-1.22]) and shorter TTI (adjusted hazard ratio, 1.14 [95% CI, 1.04-1.24]), but not with survival benefits (adjusted hazard ratio, 1.00 [0.80-1.26]). CONCLUSIONS: Medicaid expansion in Ohio was associated with improvements in receipt of standard treatment of breast cancer and shorter TTI but not with improved survival outcomes. Future studies should elucidate the mechanisms at play.

Investigating market-based opportunities for the provision of nutritious and safe diets to prevent childhood stunting: a UKRI-GCRF action against stunting hub protocol paper.

BACKGROUND: Inadequate access to affordable, safe, desirable and convenient nutrient-dense food is one of the underlying causes of child stunting. While targeted nutrition-sensitive interventions (eg, backyard 'nutri-gardens') may increase dietary diversity within farming households, such interventions have limited scalability across the wider food system where markets remain underdeveloped. This research aims to develop and assess market-based interventions for key nutrient-dense foods to help improve the diets of women and children in the first 1000 days of life. METHODS: Data collection uses four parallel approaches in each of the three study countries (India, Indonesia and Senegal). (1) A novel food environment tool will be developed to characterise the accessibility and affordability of nutrient-dense foods in the study countries. The tool will be validated through pretesting using cognitive interviewing and piloting in purposively sampled households, 10 (cognitive interviewing) and 30 (piloting) households in each country; (2) stakeholder interviews (eg, with producers, intermediaries and retailers) will be conducted to map out nutrition-sensitive entry points of key value chains (eg, animal-sourced foods), before hotspots of potential food safety hazards will be identified from food samples collected along the chains; (3) the Optifood and Agrifood tools will be used to identify foods that can address food system nutrient gaps and engage key stakeholders to prioritise market interventions to improve nutrition outcomes. Optifood and Agrifood parameters will be informed by publicly available data, plus interviews and focus groups with value chain stakeholders; (4) informed by the previous three approaches and a campaign of participatory 'group model building', a novel system dynamics model will evaluate the impact of alternative market-based solutions on the availability and affordability of nutrient-dense foods over time. ETHICS AND DISSEMINATION: The study has received ethical approval in the United Kingdom, Senegal, Indonesia and India. Dissemination comprises peer-reviewed journals, international disciplinary conferences and multistakeholder dissemination workshops.

Identifying value chain trade-offs from fruit and vegetable aggregation services in Bangladesh using a system dynamics approach.

Significant progress has been made in cereal production in Bangladesh due to an agricultural policy environment that prioritizes the productivity of staple crops over fruit and vegetables (F&V). However, many smallholder farmers remain poorly connected to markets, which may lead to a limited supply response of F&V that can reduce opportunities for sufficient intake in neglected, consumer-facing, smaller retail markets. To address this issue, aggregation schemes have been conceived that collect and transport F&Vs on behalf of multiple farmers. Given the volume of horticultural produce produced and the reliance on developed transport infrastructure, aggregation schemes tend to supply wholesale and urban markets rather than underdeveloped rural and isolated markets. To this end, we investigated how a particular aggregation intervention ('Loop') could potentially improve the distribution of F&V to smaller markets whilst improving farmer benefits. We used an innovative system dynamics modeling approach based on Loop`s aggregation services in Jashore, Bangladesh, and to identify the potential trade-offs between consumer outcomes in retail markets and farmer benefits. We find that combining aggregation with a quota at the smaller market, transport subsidy, and current price growth does not result in trade-offs between consumer purchases and farmers`benefits. However, combining aggregation with current price growth can increase demand without losing farmers`benefits. The findings emphasize that standalone and multiple market-oriented interventions generate broader win-win benefits to promote inclusive food systems.

An individualized Bayesian method for estimating genomic variants of hypertension.

BACKGROUND: Genomic variants of the disease are often discovered nowadays through population-based genome-wide association studies (GWAS). Identifying genomic variations potentially underlying a phenotype, such as hypertension, in an individual is important for designing personalized treatment; however, population-level models, such as GWAS, may not capture all the important, individualized factors well. In addition, GWAS typically requires a large sample size to detect the association of low-frequency genomic variants with sufficient power. Here, we report an individualized Bayesian inference (IBI) algorithm for estimating the genomic variants that influence complex traits, such as hypertension, at the level of an individual (e.g., a patient). By modeling at the level of the individual, IBI seeks to find genomic variants observed in the individual's genome that provide a strong explanation of the phenotype observed in this individual. RESULTS: We applied the IBI algorithm to the data from the Framingham Heart Study to explore the genomic influences of hypertension. Among the top-ranking variants identified by IBI and GWAS, there is a significant number of shared variants (intersection); the unique variants identified only by IBI tend to have relatively lower minor allele frequency than those identified by GWAS. In addition, IBI discovered more individualized and diverse variants that explain hypertension patients better than GWAS. Furthermore, IBI found several well-known low-frequency variants as well as genes related to blood pressure that GWAS missed in the same cohort. Finally, IBI identified top-ranked variants that predicted hypertension better than GWAS, according to the area under the ROC curve. CONCLUSIONS: The results support IBI as a promising approach for complementing GWAS, especially in detecting low-frequency genomic variants as well as learning personalized genomic variants of clinical traits and disease, such as the complex trait of hypertension, to help advance precision medicine.

Online Patient Education Materials on Iron Deficiency Anemia Are Too Difficult to Read and Low Quality: A Readability and Quality Analysis.

Introduction Patients increasingly rely on online health information to understand and manage their diseases. Concerns about the quality and readability of these materials have been reported in the literature. Poor quality and difficult-to-read information lead to delayed diagnoses and adverse outcomes. We assessed the quality and readability of online health information about iron deficiency anemia (IDA) on Google. Method We searched for online web pages using the term "iron deficiency anemia"on Google. One hundred and twelve out of 200 web pages were included. We assessed web page typology, readability, the Journal of the American Medical Association (JAMA) score, the DISCERN score, and the Health on the Net Foundation certification (HONcode). Statistical analysis was performed with R version 4.2.2. Result Non-profit and scientific journal web pages were the most common. Scientific journal web pages were of the highest quality. News web pages were the most readable. The first Google Page web pages did not have greater JAMA scores or lower Flesch-Kinkaid Reading Grade Level (FKGL) and Simple Measure of Gobbledygook (SMOG) scores. Forty-six percent of all web pages were high-quality. Web pages on the first Google page were more likely to have HONCode certification. Conclusion We highlight gaps in the readability and quality of online information about IDA. Online web pages exceeded the recommended reading level for patients. Most web pages were low quality; only a quarter were HONcode-certified; and the first Google page web pages were not higher in quality than the later web pages on search.

Combined Bioinformatic and Splicing Analysis of Likely Benign Intronic and Synonymous Variants Reveals Evidence for Pathogenicity.

Background: Current clinical variant analysis pipelines focus on coding variants and intronic variants within 10-20 bases of an exon-intron boundary that may affect splicing. The impact of newer splicing prediction algorithms combined with in vitro splicing assays on rare variants currently considered Benign/Likely Benign (B/LB) is unknown. Methods: Exome sequencing data from 576 pediatric cancer patients enrolled in the Texas KidsCanSeq study were filtered for intronic or synonymous variants absent from population databases, predicted to alter splicing via SpliceAI (>0.20), and scored as potentially deleterious by CADD (>10.0). Total cellular RNA was extracted from monocytes and RT-PCR products analyzed. Subsequently, rare synonymous or intronic B/LB variants in a subset of genes submitted to ClinVar were similarly evaluated. Variants predicted to lead to a frameshifted splicing product were functionally assessed using an in vitro splicing reporter assay in HEK-293T cells. Results: KidsCanSeq exome data analysis revealed a rare, heterozygous, intronic variant (NM_177438.3(DICER1):c.574-26A>G) predicted by SpliceAI to result in gain of a secondary splice acceptor site. The proband had a personal and family history of pleuropulmonary blastoma consistent with DICER1 syndrome but negative clinical sequencing reports. Proband RNA analysis revealed alternative DICER1 transcripts including the SpliceAI-predicted transcript.Similar bioinformatic analysis of synonymous or intronic B/LB variants (n=31,715) in ClinVar from 61 Mendelian disease genes yielded 18 variants, none of which could be scored by MaxEntScan. Eight of these variants were assessed (DICER1 n=4, CDH1 n=2, PALB2 n=2) using in vitro splice reporter assay and demonstrated abnormal splice products (mean 66%; range 6% to 100%). Available phenotypic information from submitting laboratories demonstrated DICER1 phenotypes in 2 families (1 variant) and breast cancer phenotypes for PALB2 in 3 families (2 variants). Conclusions: Our results demonstrate the power of newer predictive splicing algorithms to highlight rare variants previously considered B/LB in patients with features of hereditary conditions. Incorporation of SpliceAI annotation of existing variant data combined with either direct RNA analysis or in vitro assays has the potential to identify disease-associated variants in patients without a molecular diagnosis.

Patient Decisions Regarding Rescheduling Colonoscopies Postponed Due to the COVID-19 Pandemic.

BACKGROUND: Due to the COVID-19 pandemic, elective colonoscopies were postponed in Ohio from 3/17/2020 to 5/1/2020. When the ban was lifted, canceled patients determined whether to reschedule their colonoscopy in the midst of the ongoing pandemic. AIMS: We aim to determine whether demographic, colorectal cancer (CRC) risk, and COVID-19 morbidity and mortality risk factors are associated with rescheduling of colonoscopies canceled by the COVID-19 pandemic. METHODS: A medical record review of 420 participants ages 40-74 at a midwestern academic health system with elective colonoscopies canceled from 3/17/2020 to 5/1/2020 due to the COVID-19 pandemic was performed. RESULTS: More than half of participants (71.0%) rescheduled their colonoscopy within the next 8 months. Indication for colonoscopy being 'surveillance following adenoma', colonoscopy ordered by primary care provider rather than gastroenterologist, and dyslipidemia were independently associated with rescheduling colonoscopy. Higher body mass index, indication for colonoscopy being simply 'screening for CRC,' and stool testing were associated with not rescheduling. Diagnoses associated with colorectal cancer risk such as adenomas, personal or family history of colorectal cancer, and inflammatory bowel disease were not associated with rescheduling, nor were other comorbidities associated with increased COVID-19 severity. 4.5% (19/420) opted for stool fecal immunochemical test or Cologuard testing. CONCLUSIONS: Most patients rescheduled their colonoscopy despite the risk of virus exposure, suggesting that concern of missed colorectal cancer diagnosis outweighed coronavirus concerns. Patient trust in referring providers may be important for rescheduling, and colonoscopy indications were independently associated with rescheduling status.

Incidence of Kidney Stones After Bariatric Surgeries: Comparing Roux-en-Y Gastric Bypass and Sleeve Gastrectomy.

INTRODUCTION/PURPOSE: The two most common procedures performed to treat obesity are Roux-En-Y gastric bypass (RNYGB) and laparoscopic sleeve gastrectomy (LSG). Due to changes in enteric absorption, bariatric surgery increases rates of nephrolithiasis. As population-based data are limited, we aimed to compare the incidence of kidney stones after RNYGB and LSG. MATERIALS AND METHODS: We queried Explorys (Cleveland, OH), a database that aggregated data from 26 healthcare systems. We identified patients who were newly diagnosed with nephrolithiasis 3, 6, and 12 months after their RNYGB or LSG. Additionally, a multivariate analysis was conducted to investigate the association of nephrolithiasis with RNYGB as compared to LSG. This analysis adjusted for other risk factors, including age above 65, male gender, Caucasian race, diabetes mellitus, hypertension, primary hyperparathyroidism, gout, and obesity. RESULTS: From 1999 to 2019, there were 11,480 patients who underwent RNYGB and 22,770 patients who underwent LSG. The incidence of nephrolithiasis in the RNYGB cohort at all three time points was higher than in the LSG cohort (3 months, 7.1% vs. 2.4%; 6 months, 6.6% vs. 2.0%; 1 year, 5.8% vs. 1.4%; P < 0.001). After the multivariate analysis, it was found that, though both RNYGB and LSG were independently associated with the development of nephrolithiasis, the risk of nephrolithiasis was higher in those who underwent RNYGB compared to those who underwent LSG (OR 1.594, 95% CI 1.494 to 1.701, P < 0.001). CONCLUSION: RNYGB is associated with a higher risk of nephrolithiasis when compared to LSG.

Allele biased transcription factor binding across human brain regions gives mechanistic insight into eQTLs.

Transcription Factors (TFs) influence gene expression by facilitating or disrupting the formation of transcription initiation machinery at particular genomic loci. Because genomic localization of TFs is in part driven by TF recognition of DNA sequence, variation in TF binding sites can disrupt TF-DNA associations and affect gene regulation. To identify variants that impact TF binding in human brain tissues, we quantified allele bias for 93 TFs analyzed with ChIP-seq experiments of multiple structural brain regions from two donors. Using graph genomes constructed from phased genomic sequence data, we compared ChIP-seq signal between alleles at heterozygous variants within each tissue sample from each donor. Comparison of results from different brain regions within donors and the same regions between donors provided measures of allele bias reproducibility. We identified thousands of DNA variants that show reproducible bias in ChIP-seq for at least one TF. We found that alleles that are rarer in the general population were more likely than common alleles to exhibit large biases, and more frequently led to reduced TF binding. Combining ChIP-seq with RNA-seq, we identified TF-allele interaction biases with RNA bias in a phased allele linked to 6,709 eQTL variants identified in GTEx data, 3,309 of which were found in neural contexts. Our results provide insights into the effects of both common and rare variation on gene regulation in the brain. These findings can facilitate mechanistic understanding of cis-regulatory variation associated with biological traits, including disease.

Osteopontin is associated with dementia in the presence of cerebral small vessel disease.

BACKGROUND: Osteopontin (OPN) is a proinflammatory cytokine that has been recently implicated in neuroinflammation and neurodegeneration. We hypothesized that an increase in plasma osteopontin is a deleterious neuroinflammatory marker in people with dementia and cerebral small vessel disease (CSVD). METHODS: A pilot study was conducted on participants in the Northern Manhattan Study (NOMAS). Three groups were selected based on their dementia status and evidence of subclinical CSVD and chosen to be similar in age, sex, and education attainment: No dementia/No CSVD (n=19), Dementia/No CSVD (n=22), and Dementia+CSVD (n=21). Dementia (any type) was diagnosed by consensus adjudication following a series of comprehensive neuropsychological assessments and a review of the medical history. CSVD was indicated by silent brain infarcts, enlarged perivascular spaces, cerebral microbleeds, and white matter hyperintensity volumes (WMHV) on MRI. Multinomial logistic regression was used to examine the difference in OPN levels across groups, adjusting for key determinants of CSVD and neurodegeneration. RESULTS: Plasma osteopontin levels were elevated in the Dementia+CSVD group (mean=70.69±39.00 ng/ml) but not in the Dementia/No CSVD group (mean=45.46±19.11 ng/ml) compared to the No dementia/No CSVD group (mean=36.43±15.72 ng/ml). Osteopontin was associated with Dementia+CSVD (Odds Ratio (OR) per ng/ml=1.06, 95%CI 1.02-1.11) after adjusting for covariates, including brain volume. OPN was strongly correlated with WMHV (Spearman's rank correlation =0.46, p=0.0001), but not with other components of CSVD. CONCLUSION: In this pilot, greater levels of plasma osteopontin were associated with dementia with evidence of CSVD. This link was predominately driven by the contribution of OPN to dementia through the burden of white matter lesions.

Predictors of Hospital-related Outcomes of COVID-19 Infection in Patients With Inflammatory Bowel Disease in the Early Pandemic Phase: A Nationwide Inpatient Database Survey.

BACKGROUND: Patients with inflammatory bowel disease (IBD) are at higher risk for severe COVID-19 infection. However, most studies are single-center, and nationwide data in the United States are lacking. This study aimed to investigate hospital-related outcomes and predictors of these outcomes in patients with IBD and COVID-19 infection. METHODS: The National Inpatient Sample and National Readmission database were queried for all the patient hospitalizations with IBD with concurrent COVID-19 in the study group and non-COVID-19 related hospitalizations in the control group. For patients under 18 years, elective and trauma-related hospitalizations were excluded. Primary outcomes included mortality, septic shock, mechanical ventilation, and intensive care utilization. Secondary outcomes included length of stay and total hospitalization costs. RESULTS: From this query, 8865 adult patients with IBD and COVID-19 were identified. These patients were relatively older (62.8 vs 57.7 years, P < .01), and the majority were females (52.1% with COVID-19 vs 55.2% without COVID-19). Patients with IBD and COVID-19 had higher mortality (12.24% vs 2.55%; P < .01), increased incidence of septic shock (7.9% vs 4.4%; P < .01), mechanical ventilation (11.5% vs 3.7%; P < .01), and intensive care utilization (12% vs 4.6%; P < .01). These patients also had higher mean length of stay (8.28 days vs 5.47 days; P < .01) and total hospitalization costs ($21 390 vs $16 468; P < .01) than those without COVID-19 infection. CONCLUSIONS: Patients with IBD and COVID-19 have worse outcomes, with a higher incidence of severe COVID-19 disease, leading to higher mortality rates, longer lengths of stay, and increased total hospitalization costs. Encouraging preventive health measures and treating promptly with advanced COVID-19 therapies may improve outcomes and decrease the healthcare burden.

This study used nationwide data to examine hospital-related outcomes in patients with inflammatory bowel disease (IBD) and COVID-19 disease. Patients with IBD and COVID-19 had higher mortality, septic shock, mechanical ventilation, and intensive care utilization rates. They also experienced higher costs and longer hospital stays, highlighting the need for preventive measures and timely treatment to improve outcomes and reduce healthcare burden.