Plasma Metabolomics in Human Pulmonary Tuberculosis Disease: A Pilot Study

We aimed to characterize metabolites during tuberculosis (TB) disease and identify new pathophysiologic pathways involved in infection as well as biomarkers of TB onset, progression and resolution. Such data may inform development of new anti-tuberculosis drugs. Plasma samples from adults with newly diagnosed pulmonary TB disease and their matched, asymptomatic, sputum culture-negative household contacts were analyzed using liquid chromatography high-resolution mass spectrometry (LC-MS) to identify metabolites. Statistical and bioinformatics methods were used to select accurate mass/charge (m/z) ions that were significantly different between the two groups at a false discovery rate (FDR) of q<0.05. Two-way hierarchical cluster analysis (HCA) was used to identify clusters of ions contributing to separation of cases and controls, and metabolomics databases were used to match these ions to known metabolites. Identity of specific D-series resolvins, glutamate and Mycobacterium tuberculosis (Mtb)-derived trehalose-6-mycolate was confirmed using LC-MS/MS analysis. Over 23,000 metabolites were detected in untargeted metabolomic analysis and 61 metabolites were significantly different between the two groups. HCA revealed 8 metabolite clusters containing metabolites largely upregulated in patients with TB disease, including anti-TB drugs, glutamate, choline derivatives, Mycobacterium tuberculosis-derived cell wall glycolipids (trehalose-6-mycolate and phosphatidylinositol) and pro-resolving lipid mediators of inflammation, known to stimulate resolution, efferocytosis and microbial killing. The resolvins were confirmed to be RvD1, aspirin-triggered RvD1, and RvD2. This study shows that high-resolution metabolomic analysis can differentiate patients with active TB disease from their asymptomatic household contacts. Specific metabolites upregulated in the plasma of patients with active TB disease, including Mtb-derived glycolipids and resolvins, have potential as biomarkers and may reveal pathways involved in TB disease pathogenesis and resolution

Dietary energy density: a mediator of depressive symptoms and abdominal obesity or independent predictor of abdominal obesity?

In the U.S., Europe, and throughout the world, abdominal obesity prevalence is increasing. Depressive symptoms may contribute to abdominal obesity through the consumption of diets high in energy density. To test dietary energy density ([DED]; kilocalories/gram of food and beverages consumed) for an independent relationship with abdominal obesity or as a mediator between depressive symptoms and abdominal obesity. This cross-sectional study included 87 mid-life, overweight adults; 73.6% women; 50.6% African-American. Variables and measures: Beck depression inventory-II (BDI-II) to measure depressive symptoms; 3-day weighed food records to calculate DED; and waist circumference, an indicator of abdominal obesity. Hierarchical regression tested if DED explained waist circumference variance while controlling for depressive symptoms and consumed food and beverage weight. Three approaches tested DED as a mediator. Nearly three-quarters of participants had abdominal obesity, and the mean waist circumference was 103.2 (SD 14.3) cm. Mean values: BDI-II was 8.67 (SD 8.34) which indicates that most participants experienced minimal depressive symptoms, and 21.8% reported mild to severe depressive symptoms (BDI-II ≥ 14); DED was 0.75 (SD 0.22) kilocalories/gram. Hierarchical regression showed an independent association between DED and waist circumference with DED explaining 7.0% of variance above that accounted for by BDI-II and food and beverage weight. DED did not mediate between depressive symptoms and abdominal obesity. Depressive symptoms and DED were associated with elevated waist circumference, thus a comprehensive intervention aimed at improving depressive symptoms and decreasing DED to reduce waist circumference is warranted

Dietary energy density: a mediator of depressive symptoms and abdominal obesity or independent predictor of abdominal obesity?

BACKGROUND: In the U.S., Europe, and throughout the world, abdominal obesity prevalence is increasing. Depressive symptoms may contribute to abdominal obesity through the consumption of diets high in energy density. PURPOSE: To test dietary energy density ([DED]; kilocalories/gram of food and beverages consumed) for an independent relationship with abdominal obesity or as a mediator between depressive symptoms and abdominal obesity. METHODS: This cross-sectional study included 87 mid-life, overweight adults; 73.6% women; 50.6% African-American. Variables and measures: Beck Depression Inventory-II (BDI-II) to measure depressive symptoms; 3-day weighed food records to calculate DED; waist circumference, an indicator of abdominal obesity. Hierarchical regression tested if DED explained waist circumference variance while controlling for depressive symptoms and consumed food and beverage weight. Three approaches tested DED as a mediator. RESULTS: Nearly three-quarters of participants had abdominal obesity, and the mean waist circumference was 103.2 (SD 14.3) cm. Mean values: BDI-II was 8.67 (SD 8.34) which indicates most participants experienced minimal depressive symptoms, and 21.8% reported mild to severe depressive symptoms (BDI-II ≥ 14); DED was 0.75 (SD 0.22) kilocalories/gram. Hierarchical regression showed an independent association between DED and waist circumference with DED explaining 7.0% of variance above that accounted for by BDI-II and food and beverage weight. DED did not mediate between depressive symptoms and abdominal obesity. CONCLUSIONS: Depressive symptoms and DED were associated with elevated waist circumference, thus a comprehensive intervention aimed at improving depressive symptoms and decreasing DED to reduce waist circumference is warranted

Real-world Implementation of a Noninvasive, AI-augmented, Anemia-screening Smartphone App and Personalization for Hemoglobin Level Self-monitoring

Anemia, characterized by low blood hemoglobin (Hgb) levels, afflicts \u3e2 billion individuals worldwide. Here, we report real-world data generated by a smartphone app that noninvasively screens for anemia using only “fingernail selfies.” App data for anemia screening were obtained from \u3e1.4 million uses across the United States enabling geographic mapping of Hgb levels. Of those, 9,061 users also self-reported complete blood count Hgb levels for comparison, resulting in accuracy and performance that match gold standard laboratory testing and a sensitivity and specificity of 89% and 93%, respectively, when using an anemia cutoff of 12.5 g/dL. Geotagged data enabled construction of an “anemia map” of the United States, which demonstrated that Hgb levels correlate with socioeconomic status, and that the app is more likely to be used in counties with higher median income counties, more Black residents, and more primary care physicians. In addition, “personalization” of the app’s AI-augmented algorithm empowers self-monitoring of Hgb levels for those already diagnosed with anemia, such as chronic kidney disease (CKD) patients. After personalization, the app’s mean absolute error improved from 1.36 to 0.74 g/dL (P = 3.13E-11) and from 0.69 to 0.57 g/dL (P = 0.006) for CKD patients and real-world users with known anemia, respectively. Given its scalability, noninvasiveness, and geotagging capabilities, this app has the potential to enhance public health initiatives by screening an entire population for anemia coupled with geographic mapping. Moreover, personalization of the app enables individuals to serially monitor their Hgb levels instantaneously and remotely

Sagittal Abdominal Diameter and Visceral Adiposity: Correlates of Beta-Cell Function and Dysglycemia in Severely Obese Women

Postprint, author's accepted manuscriptBackground: In the context of increasing obesity prevalence, the relationship between large visceral adipose tissue (VAT) volumes and type 2 diabetes mellitus (T2DM) is unclear. In a clinical sample of severely obese women (mean body mass index [BMI], 46 kg/m2) with fasting normoglycemia (n = 40) or dysglycemia (impaired fasting glucose + diabetes; n = 20), we sought to determine the usefulness of anthropometric correlates of VAT and associations with dysglycemia. Methods: VAT volume was estimated using multi-slice computer tomography; anthropometric surrogates included sagittal abdominal diameter (SAD), waist circumference (WC) and BMI. Insulin sensitivity (Si), and beta-cell dysfunction, measured by insulin secretion (AIRg) and the disposition index (DI), were determined by frequently sampled intravenous glucose tolerance test. Results: Compared to fasting normoglycemic women, individuals with dysglycemia had greater VAT (P < 0.001) and SAD (P = 0.04), but BMI, total adiposity and Si were similar. VAT was inversely associated with AIRg and DI after controlling for ancestry, Si, and total adiposity (standardized beta, −0.32 and −0.34, both P < 0.05). In addition, SAD (beta = 0.41, P = 0.02) was found to be a better estimate of VAT volume than WC (beta = 0.32, P = 0.08) after controlling for covariates. Receiver operating characteristic analysis showed that VAT volume, followed by SAD, outperformed WC and BMI in identifying dysglycemic participants. Conclusions: Increasing VAT is associated with beta-cell dysfunction and dysglycemia in very obese women. In the presence of severe obesity, SAD is a simple surrogate of VAT, and an indicator of glucose dysregulation

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Diagnostic ‘omics’ for active tuberculosis

The decision to treat active tuberculosis (TB) is dependent on microbiological tests for the organism or evidence of disease compatible with TB in people with a high demographic risk of exposure. The tuberculin skin test and peripheral blood interferon-γ release assays do not distinguish active TB from a cleared or latent infection. Microbiological culture of mycobacteria is slow. Moreover, the sensitivities of culture and microscopy for acid-fast bacilli and nucleic acid detection by PCR are often compromised by difficulty in obtaining samples from the site of disease. Consequently, we need sensitive and rapid tests for easily obtained clinical samples, which can be deployed to assess patients exposed to TB, discriminate TB from other infectious, inflammatory or autoimmune diseases, and to identify subclinical TB in HIV-1 infected patients prior to commencing antiretroviral therapy. We discuss the evaluation of peripheral blood transcriptomics, proteomics and metabolomics to develop the next generation of rapid diagnostics for active TB. We catalogue the studies published to date seeking to discriminate active TB from healthy volunteers, patients with latent infection and those with other diseases. We identify the limitations of these studies and the barriers to their adoption in clinical practice. In so doing, we aim to develop a framework to guide our approach to discovery and development of diagnostic biomarkers for active TB

A first update on mapping the human genetic architecture of COVID-19

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