Metabolomic and inflammatory signatures of symptom dimensions in major depression.

BACKGROUND: Major depressive disorder (MDD) is a highly heterogenous disease, both in terms of clinical profiles and pathobiological alterations. Recently, immunometabolic dysregulations were shown to be correlated with atypical, energy-related symptoms but less so with the Melancholic or Anxious distress symptom dimensions of depression in The Netherlands Study of Depression and Anxiety (NESDA) study. In this study, we aimed to replicate these immunometabolic associations and to characterize the metabolomic correlates of each of the three MDD dimensions. METHODS: Using three clinical rating scales, Melancholic, and Anxious distress, and Immunometabolic (IMD) dimensions were characterized in 158 patients who participated in the Predictors of Remission to Individual and Combined Treatments (PReDICT) study and from whom plasma and serum samples were available. The NESDA-defined inflammatory index, a composite measure of interleukin-6 and C-reactive protein, was measured from pre-treatment plasma samples and a metabolomic profile was defined using serum samples analyzed on three metabolomics platforms targeting fatty acids and complex lipids, amino acids, acylcarnitines, and gut microbiome-derived metabolites among other metabolites of central metabolism. RESULTS: The IMD clinical dimension and the inflammatory index were positively correlated (r = 0.19, p = 0.019) after controlling for age, sex, and body mass index, whereas the Melancholic and Anxious distress dimensions were not, replicating the previous NESDA findings. The three symptom dimensions had distinct metabolomic signatures using both univariate and set enrichment statistics. IMD severity correlated mainly with gut-derived metabolites and a few acylcarnitines and long chain saturated free fatty acids. Melancholia severity was significantly correlated with several phosphatidylcholines, primarily the ether-linked variety, lysophosphatidylcholines, as well as several amino acids. Anxious distress severity correlated with several medium and long chain free fatty acids, both saturated and polyunsaturated ones, sphingomyelins, as well as several amino acids and bile acids. CONCLUSION: The IMD dimension of depression appears reliably associated with markers of inflammation. Metabolomics provides powerful tools to inform about depression heterogeneity and molecular mechanisms related to clinical dimensions in MDD, which include a link to gut microbiome and lipids implicated in membrane structure and function.

A genome-wide association study of obstructive heart defects among participants in the National Birth Defects Prevention Study.

Obstructive heart defects (OHDs) share common structural lesions in arteries and cardiac valves, accounting for ~25% of all congenital heart defects. OHDs are highly heritable, resulting from interplay among maternal exposures, genetic susceptibilities, and epigenetic phenomena. A genome-wide association study was conducted in National Birth Defects Prevention Study participants (Ndiscovery  = 3978; Nreplication  = 2507), investigating the genetic architecture of OHDs using transmission/disequilibrium tests (TDT) in complete case-parental trios (Ndiscovery_TDT  = 440; Nreplication_TDT  = 275) and case-control analyses separately in infants (Ndiscovery_CCI  = 1635; Nreplication_CCI  = 990) and mothers (case status defined by infant; Ndiscovery_CCM  = 1703; Nreplication_CCM  = 1078). In the TDT analysis, the SLC44A2 single nucleotide polymorphism (SNP) rs2360743 was significantly associated with OHD (pdiscovery  = 4.08 × 10-9 ; preplication  = 2.44 × 10-4 ). A CAPN11 SNP (rs55877192) was suggestively associated with OHD (pdiscovery  = 1.61 × 10-7 ; preplication  = 0.0016). Two other SNPs were suggestively associated (p < 1 × 10-6 ) with OHD in only the discovery sample. In the case-control analyses, no SNPs were genome-wide significant, and, even with relaxed thresholds ( × discovery < 1 × 10-5 and preplication < 0.05), only one SNP (rs188255766) in the infant analysis was associated with OHDs (pdiscovery  = 1.42 × 10-6 ; preplication  = 0.04). Additional SNPs with pdiscovery < 1 × 10-5 were in loci supporting previous findings but did not replicate. Overall, there was modest evidence of an association between rs2360743 and rs55877192 and OHD and some evidence validating previously published findings.

Infant Formula Feeding Changes the Proliferative Status in Piglet Neonatal Mammary Glands Independently of Estrogen Signaling.

BACKGROUND: Soy infant formula contains isoflavones, which are able to bind to and activate estrogen receptor (ER) pathways. The mammary gland is sensitive to estrogens, raising concern that the use of soy formulas may promote premature development. OBJECTIVE: We aimed to determine if soy formula feeding increases mammary gland proliferation and differentiation in comparison to other infant postnatal diets. METHODS: White-Dutch Landrace piglets aged 2 d received either sow milk (Sow), or were provided milk formula (Milk), soy formula (Soy), milk formula supplemented with 17-beta-estradiol (2 mg/(kg·d); M + E2), or milk formula supplemented with genistein (84 mg/L of diet; M + G) until day 21. Mammary gland proliferation and differentiation was assessed by histology, and real-time RT-PCR confirmation of differentially expressed genes identified by microarray analysis. RESULTS: Mammary terminal end bud numbers were 19-31% greater in the Milk, Soy, and M + G groups relative to the Sow and M + E2, P <0.05. Microarray analysis identified differentially expressed genes between each formula-fed group relative to the Sow (±1.7-fold, P <0.05). Real-time RT-PCR confirmed 2- to 4-fold increases in mRNA transcripts of genes involved in cell proliferation, insulin-like growth factor 1 (IGF1), fibroblast growth factor 10 (FGF10), and fibroblast growth factor 18 (FGF18), in all groups relative to the Sow, P <0.05. In contrast, genes involved in cell differentiation and ductal morphogenesis, angiotensin II receptor type 2 (AGTR2), microtubule associated protein 1b (MAP1B), and kinesin family member 26b (KIF26B), were significantly upregulated by 2-, 4-, and 13-fold, respectively, in the M + E2 group. Additionally, mRNA expression of ER-specific gene targets, progesterone receptor (PGR), was increased by 12-fold, and amphiregulin (AREG) and Ras-like estrogen regulated growth inhibitor (RERG) expression by 1.5-fold in the M + E2 group, P <0.05. In the soy and M + G groups, mRNA expressions of fatty acid synthesis genes were increased 2- to 4-fold. CONCLUSIONS: Our data indicate soy formula feeding does not promote ER-signaling in the piglet mammary gland. Infant formula feeding (milk- or soy-based) may initiate proliferative pathways independently of estrogenic signaling.

Skeletal muscle interstitial fluid metabolomics at rest and associated with an exercise bout: application in rats and humans.

Blood or biopsies are often used to characterize metabolites that are modulated by exercising muscle. However, blood has inputs derived from multiple tissues, biopsies cannot discriminate between secreted and intracellular metabolites, and their invasive nature is challenging for frequent collections in sensitive populations (e.g., children and pregnant women). Thus, minimally invasive approaches to interstitial fluid (IF) metabolomics would be valuable. A catheter was designed to collect IF from the gastrocnemius muscle of acutely anesthetized adult male rats at rest or immediately following 20 min of exercise (~60% of maximal O2 uptake). Nontargeted, gas chromatography-time-of-flight mass spectrometry analysis was used to detect 299 metabolites, including nonannotated metabolites, sugars, fatty acids, amino acids, and purine metabolites and derivatives. Just 43% of all detected metabolites were common to IF and blood plasma, and only 20% of exercise-modified metabolites were shared in both pools, highlighting that the blood does not fully reflect the metabolic outcomes in muscle. Notable exercise patterns included increased IF amino acids (except leucine and isoleucine), increased α-ketoglutarate and citrate (which may reflect tricarboxylic acid cataplerosis or shifts in nonmitochondrial pathways), and higher concentration of the signaling lipid oleamide. A preliminary study of human muscle IF was conducted using a 20-kDa microdialysis catheter placed in the vastus lateralis of five healthy adults at rest and during exercise (65% of estimated maximal heart rate). Approximately 70% of commonly detected metabolites discriminating rest vs. exercise in rats were also changed in exercising humans. Interstitium metabolomics may aid in the identification of molecules that signal muscle work (e.g., exertion and fatigue) and muscle health.

Dynamic assessment of microbial ecology (DAME): a web app for interactive analysis and visualization of microbial sequencing data.

Summary: Dynamic assessment of microbial ecology (DAME) is a Shiny-based web application for interactive analysis and visualization of microbial sequencing data. DAME provides researchers not familiar with R programming the ability to access the most current R functions utilized for ecology and gene sequencing data analyses. Currently, DAME supports group comparisons of several ecological estimates of α-diversity and ß-diversity, along with differential abundance analysis of individual taxa. Using the Shiny framework, the user has complete control of all aspects of the data analysis, including sample/experimental group selection and filtering, estimate selection, statistical methods and visualization parameters. Furthermore, graphical and tabular outputs are supported by R packages using D3.js and are fully interactive. Availability and implementation: DAME was implemented in R but can be modified by Hypertext Markup Language (HTML), Cascading Style Sheets (CSS), and JavaScript. It is freely available on the web at https://acnc-shinyapps.shinyapps.io/DAME/. Local installation and source code are available through Github (https://github.com/bdpiccolo/ACNC-DAME). Any system with R can launch DAME locally provided the shiny package is installed. Contact: bdpiccolo@uams.edu.

Altered bile acid profile associates with cognitive impairment in Alzheimer's disease-An emerging role for gut microbiome.

INTRODUCTION: Increasing evidence suggests a role for the gut microbiome in central nervous system disorders and a specific role for the gut-brain axis in neurodegeneration. Bile acids (BAs), products of cholesterol metabolism and clearance, are produced in the liver and are further metabolized by gut bacteria. They have major regulatory and signaling functions and seem dysregulated in Alzheimer's disease (AD). METHODS: Serum levels of 15 primary and secondary BAs and their conjugated forms were measured in 1464 subjects including 370 cognitively normal older adults, 284 with early mild cognitive impairment, 505 with late mild cognitive impairment, and 305 AD cases enrolled in the AD Neuroimaging Initiative. We assessed associations of BA profiles including selected ratios with diagnosis, cognition, and AD-related genetic variants, adjusting for confounders and multiple testing. RESULTS: In AD compared to cognitively normal older adults, we observed significantly lower serum concentrations of a primary BA (cholic acid [CA]) and increased levels of the bacterially produced, secondary BA, deoxycholic acid, and its glycine and taurine conjugated forms. An increased ratio of deoxycholic acid:CA, which reflects 7α-dehydroxylation of CA by gut bacteria, strongly associated with cognitive decline, a finding replicated in serum and brain samples in the Rush Religious Orders and Memory and Aging Project. Several genetic variants in immune response-related genes implicated in AD showed associations with BA profiles. DISCUSSION: We report for the first time an association between altered BA profile, genetic variants implicated in AD, and cognitive changes in disease using a large multicenter study. These findings warrant further investigation of gut dysbiosis and possible role of gut-liver-brain axis in the pathogenesis of AD.

Infant Formula Feeding Increases Hepatic Cholesterol 7α Hydroxylase (CYP7A1) Expression and Fecal Bile Acid Loss in Neonatal Piglets.

Background: During the postnatal feeding period, formula-fed infants have higher cholesterol synthesis rates and lower circulating cholesterol concentrations than their breastfed counterparts. Although this disparity has been attributed to the uniformly low dietary cholesterol content of typical infant formulas, little is known of the underlying mechanisms associated with this altered cholesterol metabolism phenotype. Objective: We aimed to determine the molecular etiology of diet-associated changes in early-life cholesterol metabolism with the use of a postnatal piglet feeding model. Methods: Two-day-old male and female White-Dutch Landrace piglets were fed either sow milk (Sow group) or dairy-based (Milk group; Similac Advance powder) or soy-based (Soy group; Emfamil Prosobee Lipil powder) infant formulas until day 21. In addition to measuring serum cholesterol concentrations, hepatic and intestinal genes involved in enterohepatic circulation of cholesterol and bile acids were analyzed by real-time reverse-transcriptase polymerase chain reaction and Western blot. Bile acid concentrations were measured by liquid chromatography-mass spectrometry in serum, liver, and feces. Results: Compared with the Sow group, hepatic cholesterol 7α hydroxylase (CYP7A1) protein expression was 3-fold higher in the Milk group (P < 0.05) and expression was 10-fold higher in the Soy group compared with the Milk group (P < 0.05). Likewise, fecal bile acid concentrations were 3-fold higher in the Soy group compared with the Milk group (P < 0.05). Intestinal mRNA expression of fibroblast factor 19 (Fgf19) was reduced in the Milk and Soy groups, corresponding to 54% and 67% decreases compared with the Sow group. In the Soy group, small heterodimer protein (SHP) protein expression was 30% lower compared with the Sow group (P < 0.05). Conclusions: These results indicate that formula feeding leads to increased CYP7A1 protein expression and fecal bile acid loss in neonatal piglets, and this outcome is linked to reduced efficacy in inhibiting CYP7A1 expression through FGF19 and SHP transcriptional repression mechanisms.

Multiple microRNAs function as self-protective modules in acetaminophen-induced hepatotoxicity in humans.

Acetaminophen (APAP) overdose is the leading cause of acute liver failure. Yet the mechanisms underlying adaptive tolerance toward APAP-induced liver injury are not fully understood. To better understand molecular mechanisms contributing to adaptive tolerance to APAP is an underpinning foundation for APAP-related precision medicine. In the current study, the mRNA and microRNA (miRNA) expression profiles derived from next generation sequencing data for APAP-treated (5 and 10 mM) HepaRG cells and controls were analyzed systematically. Putative miRNAs targeting key dysregulated genes involved in APAP hepatotoxicity were selected using in silico prediction algorithms, un-biased gene ontology, and network analyses. Luciferase reporter assays, RNA electrophoresis mobility shift assays, and miRNA pull-down assays were performed to investigate the role of miRNAs affecting the expression of dysregulated genes. Levels of selected miRNAs were measured in serum samples obtained from children with APAP overdose (58.6-559.4 mg/kg) and from healthy controls. As results, 2758 differentially expressed genes and 47 miRNAs were identified. Four of these miRNAs (hsa-miR-224-5p, hsa-miR-320a, hsa-miR-449a, and hsa-miR-877-5p) suppressed drug metabolizing enzyme (DME) levels involved in APAP-induced liver injury by downregulating HNF1A, HNF4A and NR1I2 expression. Exogenous transfection of these miRNAs into HepaRG cells effectively rescued them from APAP toxicity, as indicated by decreased alanine aminotransferase levels. Importantly, hsa-miR-320a and hsa-miR-877-5p levels were significantly elevated in serum samples obtained from children with APAP overdose compared to health controls. Collectively, these data indicate that hsa-miR-224-5p, hsa-miR-320a, hsa-miR-449a, and hsa-miR-877-5p suppress DME expression involved in APAP-induced hepatotoxicity and they contribute to an adaptive response in hepatocytes.

Anesthesia and bariatric surgery gut preparation alter plasma acylcarnitines reflective of mitochondrial fat and branched-chain amino acid oxidation.

The period around bariatric surgery offers a unique opportunity to characterize metabolism responses to dynamic shifts in energy, gut function, and anesthesia. We analyzed plasma acylcarnitines in obese women (n = 17) sampled in the overnight fasted/postabsorptive state approximately 1-2 wk before surgery (condition A), the morning of surgery (prior restriction to a 48-h clear liquid diet coupled in some cases a standard polyethylene glycol gut evacuation: condition B), and following induction of anesthesia (condition C). Comparisons tested if 1) plasma acylcarnitine derivatives reflective of fatty acid oxidation (FAO) and xenometabolism would be significantly increased and decreased, respectively, by preoperative gut preparation/negative energy balance (condition A vs. B), and 2) anesthesia would acutely depress markers of FAO. Acylcarnitines associated with fat mobilization and FAO were significantly increased in condition B: long-chain acylcarnitines (i.e., C18:1, ~70%), metabolites from active but incomplete FAO [i.e., C14:1 (161%) and C14:2 (102%)] and medium- to short-chain acylcarnitines [i.e., C2 (91%), R-3-hydroxybutyryl-(245%), C6 (45%), and cis-3,4-methylene-heptanoyl-(17%), etc.]. Branched-chain amino acid markers displayed disparate patterns [i.e., isobutyryl-(40% decreased) vs. isovaleryl carnitine (51% increased)]. Anesthesia reduced virtually every acylcarnitine. These results are consistent with a fasting-type metabolic phenotype coincident with the presurgical "gut preparation" phase of bariatric surgery, and a major and rapid alteration of both fat and amino acid metabolism with onset of anesthesia. Whether presurgical or anesthesia-associated metabolic shifts in carnitine and fuel metabolism impact patient outcomes or surgical risks remains to be evaluated experimentally.

Early Postnatal Diets Affect the Bioregional Small Intestine Microbiome and Ileal Metabolome in Neonatal Pigs.

Background: Breastfeeding is known to be protective against gastrointestinal disorders and may modify gut development. Although the gut microbiome has been implicated, little is known about how early diet affects the small intestine microbiome.Objective: We hypothesized that disparate early diets would promote unique microbial profiles in the small intestines of neonatal pigs.Methods: Male and female 2-d-old White Dutch Landrace pigs were either sow fed or provided dairy (Similac Advance powder; Ross Products Abbott Laboratories) or soy (Enfamil Prosobee Lipil powder; Mead Johnson Nutritionals) infant formulas until day 21. Bacterial ecology was assessed in the contents of the small intestine through the use of 16S ribosomal RNA sequencing. α-Diversity, ß-diversity, and differential abundances of operational taxonomic units were assessed by ANOVA, permutational ANOVA, and negative binomial regression, respectively. Ileum tissue metabolomics were measured by LC-mass spectrometry and assessed by weighted correlation network analysis.Results: Greater α-diversity was observed in the duodena of sow-fed compared with formula-fed neonatal pigs (P < 0.05). No differences were observed in the ilea. Firmicutes represented the most abundant phylum across all diets in duodena (78.8%, 80.1%, and 53.4% relative abundance in sow, dairy, and soy groups, respectively), followed by Proteobacteria in sow (12.2%) and dairy (12.4%) groups and Cyanobacteria in soy-fed (36.2%) pigs. In contrast to those in the duodenum, Proteobacteria was the dominant phylum in the ileum, with >60% relative abundance in all of the groups. In the duodenum, 77 genera were altered by diet, followed by 48 in the jejunum and 19 in the ileum. Metabolomics analyses revealed associations between ileum tissue metabolites (e.g., acylcarnitines, 3-aminoisobutyric acid) and diet-responsive microbial genera.Conclusions: These results indicate that the neonatal diet has regional effects on the small intestine microbiome in pigs, with the most pronounced effects occurring in the duodena. Regional effects may be important factors when considering gut tissue metabolism and development in the postnatal period.

Potential of extracellular microRNAs as biomarkers of acetaminophen toxicity in children.

UNLABELLED: Developing biomarkers for detecting acetaminophen (APAP) toxicity has been widely investigated. Recent studies of adults with APAP-induced liver injury have reported human serum microRNA-122 (miR-122) as a novel biomarker of APAP-induced liver injury. The goal of this study was to examine extracellular microRNAs (miRNAs) as potential biomarkers for APAP liver injury in children. Global levels of serum and urine miRNAs were examined in three pediatric subgroups: 1) healthy children (n=10), 2) hospitalized children receiving therapeutic doses of APAP (n=10) and 3) children hospitalized for APAP overdose (n=8). Out of 147 miRNAs detected in the APAP overdose group, eight showed significantly increased median levels in serum (miR-122, -375, -423-5p, -30d-5p, -125b-5p, -4732-5p, -204-5p, and -574-3p), compared to the other groups. Analysis of urine samples from the same patients had significantly increased median levels of four miRNAs (miR-375, -940, -9-3p and -302a) compared to the other groups. Importantly, correlation of peak serum APAP protein adduct levels (an indicator of the oxidation of APAP to the reactive metabolite N-acetyl-para-quinone imine) with peak miRNA levels showed that the highest correlation was observed for serum miR-122 (R=0.94; p<0.01) followed by miR-375 (R=0.70; p=0.05). CONCLUSION: Our findings demonstrate that miRNAs are increased in children with APAP toxicity and correlate with APAP protein adducts, suggesting a potential role as biomarkers of APAP toxicity.

Translational biomarkers of acetaminophen-induced acute liver injury.

Acetaminophen (APAP) is a commonly used analgesic drug that can cause liver injury, liver necrosis and liver failure. APAP-induced liver injury is associated with glutathione depletion, the formation of APAP protein adducts, the generation of reactive oxygen and nitrogen species and mitochondrial injury. The systems biology omics technologies (transcriptomics, proteomics and metabolomics) have been used to discover potential translational biomarkers of liver injury. The following review provides a summary of the systems biology discovery process, analytical validation of biomarkers and translation of omics biomarkers from the nonclinical to clinical setting in APAP-induced liver injury.

Acylcarnitines metabolism in depression: association with diagnostic status, depression severity and symptom profile in the NESDA cohort.

Background: Acylcarnitines (ACs) are involved in bioenergetics processes that may play a role in the pathophysiology of depression. Studies linking AC levels to depression are few and provide mixed findings. We examined the association of circulating ACs levels with Major Depressive Disorder (MDD) diagnosis, overall depression severity and specific symptom profiles. Methods: The sample from the Netherlands Study of Depression and Anxiety included participants with current (n=1035) or remitted (n=739) MDD and healthy controls (n=800). Plasma levels of four ACs (short-chain: acetylcarnitine C2 and propionylcarnitine C3; medium-chain: octanoylcarnitine C8 and decanoylcarnitine C10) were measured. Overall depression severity as well as atypical/energy-related (AES), anhedonic and melancholic symptom profiles were derived from the Inventory of Depressive Symptomatology. Results: As compared to healthy controls, subjects with current or remitted MDD presented similarly lower mean C2 levels (Cohen's d=0.2, p≤1e-4). Higher overall depression severity was significantly associated with higher C3 levels (ß=0.06, SE=0.02, p=1.21e-3). No associations were found for C8 and C10. Focusing on symptom profiles, only higher AES scores were linked to lower C2 (ß=-0.05, SE=0.02, p=1.85e-2) and higher C3 (ß=0.08, SE=0.02, p=3.41e-5) levels. Results were confirmed in analyses pooling data with an additional internal replication sample from the same subjects measured at 6-year follow-up (totaling 4195 observations). Conclusions: Small alterations in levels of short-chain acylcarnitine levels were related to the presence and severity of depression, especially for symptoms reflecting altered energy homeostasis. Cellular metabolic dysfunctions may represent a key pathway in depression pathophysiology potentially accessible through AC metabolism.

Metabolomics Signatures of serotonin reuptake inhibitor (Escitalopram), serotonin norepinephrine reuptake inhibitor (Duloxetine) and Cognitive Behavior Therapy on Key Neurotransmitter Pathways in Major Depressive Disorder.

Metabolomics provides powerful tools that can inform about heterogeneity in disease and response to treatments. In this study, we employed an electrochemistry-based targeted metabolomics platform to assess the metabolic effects of three randomly-assigned treatments: escitalopram, duloxetine, and Cognitive Behavior Therapy (CBT) in 163 treatment-naïve outpatients with major depressive disorder. Serum samples from baseline and 12 weeks post-treatment were analyzed using targeted liquid chromatography-electrochemistry for metabolites related to tryptophan, tyrosine metabolism and related pathways. Changes in metabolite concentrations related to each treatment arm were identified and compared to define metabolic signatures of exposure. In addition, association between metabolites and depressive symptom severity (assessed with the 17-item Hamilton Rating Scale for Depression [HRSD17]) and anxiety symptom severity (assessed with the 14-item Hamilton Rating Scale for Anxiety [HRSA14]) were evaluated, both at baseline and after 12 weeks of treatment. Significant reductions in serum serotonin level and increases in tryptophan-derived indoles that are gut bacterially derived were observed with escitalopram and duloxetine arms but not in CBT arm. These include indole-3-propionic acid (I3PA), indole-3-lactic acid (I3LA) and Indoxyl sulfate (IS), a uremic toxin. Purine-related metabolites were decreased across all arms. Different metabolites correlated with improved symptoms in the different treatment arms revealing potentially different mechanisms between response to antidepressant medications and to CBT.

Medication Use is Associated with Distinct Microbial Features in Anxiety and Depression.

This study investigated the relationship between gut microbiota and neuropsychiatric disorders (NPDs), specifically anxiety disorder (ANXD) and/or major depressive disorder (MDD), as defined by DSM-IV or V criteria. The study also examined the influence of medication use, particularly antidepressants and/or anxiolytics, classified through the Anatomical Therapeutic Chemical (ATC) Classification System, on the gut microbiota. Both 16S rRNA gene amplicon sequencing and shallow shotgun sequencing were performed on DNA extracted from 666 fecal samples from the Tulsa-1000 and NeuroMAP CoBRE cohorts. The results highlight the significant influence of medication use; antidepressant use is associated with significant differences in gut microbiota beta diversity and has a larger effect size than NPD diagnosis. Next, specific microbes were associated with ANXD and MDD, highlighting their potential for non-pharmacological intervention. Finally, the study demonstrated the capability of Random Forest classifiers to predict diagnoses of NPD and medication use from microbial profiles, suggesting a promising direction for the use of gut microbiota as biomarkers for NPD. The findings suggest that future research on the gut microbiota's role in NPD and its interactions with pharmacological treatments are needed.

Social Determinants of Health Data Quality at Different Levels of Geographic Detail.

Social determinants of health (SDOH) impact 80% of health outcomes from acute to chronic disorders, and attempts are underway to provide these data elements to clinicians. It is, however, difficult to collect SDOH data through (1) surveys, which provide inconsistent and incomplete data, or (2) aggregates at the neighborhood level. Data from these sources is not sufficiently accurate, complete, and up-to-date. To demonstrate this, we have compared the Area Deprivation Index (ADI) to purchased commercial consumer data at the individual-household level. The ADI is composed of income, education, employment, and housing quality information. Although this index does a good job of representing populations, it is not adequate to describe individuals, especially in a healthcare context. Aggregate measures are, by definition, not sufficiently granular to describe each individual within the population they represent and may result in biased or imprecise data when simply assigned to the individual. Moreover, this problem is generalizable to any community-level element, not just ADI, in so far as they are an aggregate of the individual community members.

Covid-19 Positivity Differences Among Patients of a Rural, Southern US State Hospital System Based on Population Density, Rural-Urban Classification, and Area Deprivation Index.

In this study we examined the correlation of COVID-19 positivity with area deprivation index (ADI), social determinants of health (SDOH) factors based on a consumer and electronic medical record (EMR) data and population density in a patient population from a tertiary healthcare system in Arkansas. COVID-19 positivity was significantly associated with population density, age, race, and household size. Understanding health disparities and SDOH data can add value to health and the creation of trustable AI.

Repeatable enhancement of healthcare data with social determinants of health.

Background: Social and behavioral aspects of our lives significantly impact our health, yet minimal social determinants of health (SDOH) data elements are collected in the healthcare system. Methods: In this proof-of-concept study we developed a repeatable SDOH enrichment and integration process to incorporate dynamically evolving SDOH domain concepts from consumers into clinical data. This process included SDOH mapping, linking compiled consumer data to patient records in Electronic Health Records, data quality analysis and preprocessing, and storage. Results: Consumer compilers data coverage ranged from ~90 to ~54% and the percentage match rate between compilers was between ~21 and 64%. Our preliminary analysis showed that apart from demographic factors, several SDOH factors like home-ownership, marital-status, presence of children, number of members per household, economic stability and education were significantly different between the COVID-19 positive and negative patient groups while estimated family-income and home market-value were not. Conclusion: Our preliminary analysis shows commercial consumer data can be a viable source of SDOH factor at an individual-level for clinical data thus providing a path for clinicians to improve patient treatment and care.

Gut Microbiome-Linked Metabolites in the Pathobiology of Major Depression With or Without Anxiety-A Role for Bile Acids.

Background: The gut microbiome may play a role in the pathogenesis of neuropsychiatric diseases including major depressive disorder (MDD). Bile acids (BAs) are steroid acids that are synthesized in the liver from cholesterol and further processed by gut-bacterial enzymes, thus requiring both human and gut microbiome enzymatic processes in their metabolism. BAs participate in a range of important host functions such as lipid transport and metabolism, cellular signaling and regulation of energy homeostasis. BAs have recently been implicated in the pathophysiology of Alzheimer's and several other neuropsychiatric diseases, but the biochemical underpinnings of these gut microbiome-linked metabolites in the pathophysiology of depression and anxiety remains largely unknown. Method: Using targeted metabolomics, we profiled primary and secondary BAs in the baseline serum samples of 208 untreated outpatients with MDD. We assessed the relationship of BA concentrations and the severity of depressive and anxiety symptoms as defined by the 17-item Hamilton Depression Rating Scale (HRSD17) and the 14-item Hamilton Anxiety Rating Scale (HRSA-Total), respectively. We also evaluated whether the baseline metabolic profile of BA informs about treatment outcomes. Results: The concentration of the primary BA chenodeoxycholic acid (CDCA) was significantly lower at baseline in both severely depressed (log2 fold difference (LFD) = -0.48; p = 0.021) and highly anxious (LFD = -0.43; p = 0.021) participants compared to participants with less severe symptoms. The gut bacteria-derived secondary BAs produced from CDCA such as lithocholic acid (LCA) and several of its metabolites, and their ratios to primary BAs, were significantly higher in the more anxious participants (LFD's range = [0.23, 1.36]; p's range = [6.85E-6, 1.86E-2]). The interaction analysis of HRSD17 and HRSA-Total suggested that the BA concentration differences were more strongly correlated to the symptoms of anxiety than depression. Significant differences in baseline CDCA (LFD = -0.87, p = 0.0009), isoLCA (LFD = -1.08, p = 0.016) and several BA ratios (LFD's range [0.46, 1.66], p's range [0.0003, 0.049]) differentiated treatment failures from remitters. Conclusion: In patients with MDD, BA profiles representing changes in gut microbiome compositions are associated with higher levels of anxiety and increased probability of first-line treatment failure. If confirmed, these findings suggest the possibility of developing gut microbiome-directed therapies for MDD characterized by gut dysbiosis.

The h-ANN Model: Comprehensive Colonoscopy Concept Compilation Using Combined Contextual Embeddings.

Colonoscopy is a screening and diagnostic procedure for detection of colorectal carcinomas with specific quality metrics that monitor and improve adenoma detection rates. These quality metrics are stored in disparate documents i.e., colonoscopy, pathology, and radiology reports. The lack of integrated standardized documentation is impeding colorectal cancer research. Clinical concept extraction using Natural Language Processing (NLP) and Machine Learning (ML) techniques is an alternative to manual data abstraction. Contextual word embedding models such as BERT (Bidirectional Encoder Representations from Transformers) and FLAIR have enhanced performance of NLP tasks. Combining multiple clinically-trained embeddings can improve word representations and boost the performance of the clinical NLP systems. The objective of this study is to extract comprehensive clinical concepts from the consolidated colonoscopy documents using concatenated clinical embeddings. We built high-quality annotated corpora for three report types. BERT and FLAIR embeddings were trained on unlabeled colonoscopy related documents. We built a hybrid Artificial Neural Network (h-ANN) to concatenate and fine-tune BERT and FLAIR embeddings. To extract concepts of interest from three report types, 3 models were initialized from the h-ANN and fine-tuned using the annotated corpora. The models achieved best F1-scores of 91.76%, 92.25%, and 88.55% for colonoscopy, pathology, and radiology reports respectively.