Sex and race differences of cerebrospinal fluid metabolites in healthy individuals.

INTRODUCTION: Analyses of cerebrospinal fluid (CSF) metabolites in large, healthy samples have been limited and potential demographic moderators of brain metabolism are largely unknown. OBJECTIVE: Our objective in this study was to examine sex and race differences in 33 CSF metabolites within a sample of 129 healthy individuals (37 African American women, 29 white women, 38 African American men, and 25 white men). METHODS: CSF metabolites were measured with a targeted electrochemistry-based metabolomics platform. Sex and race differences were quantified with both univariate and multivariate analyses. Type I error was controlled for by using a Bonferroni adjustment (0.05/33 = .0015). RESULTS: Multivariate Canonical Variate Analysis (CVA) of the 33 metabolites showed correct classification of sex at an average rate of 80.6% and correct classification of race at an average rate of 88.4%. Univariate analyses revealed that men had significantly higher concentrations of cysteine (p < 0.0001), uric acid (p < 0.0001), and N-acetylserotonin (p = 0.049), while women had significantly higher concentrations of 5-hydroxyindoleacetic acid (5-HIAA) (p = 0.001). African American participants had significantly higher concentrations of 3-hydroxykynurenine (p = 0.018), while white participants had significantly higher concentrations of kynurenine (p < 0.0001), indoleacetic acid (p < 0.0001), xanthine (p = 0.001), alpha-tocopherol (p = 0.007), cysteine (p = 0.029), melatonin (p = 0.036), and 7-methylxanthine (p = 0.037). After the Bonferroni adjustment, the effects for cysteine, uric acid, and 5-HIAA were still significant from the analysis of sex differences and kynurenine and indoleacetic acid were still significant from the analysis of race differences. CONCLUSION: Several of the metabolites assayed in this study have been associated with mental health disorders and neurological diseases. Our data provide some novel information regarding normal variations by sex and race in CSF metabolite levels within the tryptophan, tyrosine and purine pathways, which may help to enhance our understanding of mechanisms underlying sex and race differences and potentially prove useful in the future treatment of disease.

Rapid single cell evaluation of human disease and disorder targets using REVEAL: SingleCell™.

BACKGROUND: Single-cell (sc) sequencing performs unbiased profiling of individual cells and enables evaluation of less prevalent cellular populations, often missed using bulk sequencing. However, the scale and the complexity of the sc datasets poses a great challenge in its utility and this problem is further exacerbated when working with larger datasets typically generated by consortium efforts. As the scale of single cell datasets continues to increase exponentially, there is an unmet technological need to develop database platforms that can evaluate key biological hypotheses by querying extensive single-cell datasets. Large single-cell datasets like Human Cell Atlas and COVID-19 cell atlas (collection of annotated sc datasets from various human organs) are excellent resources for profiling target genes involved in human diseases and disorders ranging from oncology, auto-immunity, as well as infectious diseases like COVID-19 caused by SARS-CoV-2 virus. SARS-CoV-2 infections have led to a worldwide pandemic with massive loss of lives, infections exceeding 7 million cases. The virus uses ACE2 and TMPRSS2 as key viral entry associated proteins expressed in human cells for infections. Evaluating the expression profile of key genes in large single-cell datasets can facilitate testing for diagnostics, therapeutics, and vaccine targets, as the world struggles to cope with the on-going spread of COVID-19 infections. MAIN BODY: In this manuscript we describe REVEAL: SingleCell, which enables storage, retrieval, and rapid query of single-cell datasets inclusive of millions of cells. The array native database described here enables selecting and analyzing cells across multiple studies. Cells can be selected using individual metadata tags, more complex hierarchical ontology filtering, and gene expression threshold ranges, including co-expression of multiple genes. The tags on selected cells can be further evaluated for testing biological hypotheses. One such example includes identifying the most prevalent cell type annotation tag on returned cells. We used REVEAL: SingleCell to evaluate the expression of key SARS-CoV-2 entry associated genes, and queried the current database (2.2 Million cells, 32 projects) to obtain the results in < 60 s. We highlighted cells expressing COVID-19 associated genes are expressed on multiple tissue types, thus in part explains the multi-organ involvement in infected patients observed worldwide during the on-going COVID-19 pandemic. CONCLUSION: In this paper, we introduce the REVEAL: SingleCell database that addresses immediate needs for SARS-CoV-2 research and has the potential to be used more broadly for many precision medicine applications. We used the REVEAL: SingleCell database as a reference to ask questions relevant to drug development and precision medicine regarding cell type and co-expression for genes that encode proteins necessary for SARS-CoV-2 to enter and reproduce in cells.

Diagnostic uncertainties, ethical tensions, and accounts of role responsibilities in genetic counseling communication.

Diagnostic uncertainties are intricately associated with genomic testing-especially concerning new technologies such as exome sequencing-with test results being either inconclusive or generating secondary findings or showing variants of uncertain significance. In the process of genetic counseling, diagnostic uncertainties have to be managed even when test results for an individual client are either positive or negative because of differential implications for family members. Previous studies have investigated diagnostic uncertainties in relation to clients wanting to know or not know the test results; here, we extend this line of research by addressing how genetic counselors and clients account for the management of diagnostic uncertainties vis-à-vis the attendant ethical tensions in the complex communicative environment in the clinic setting. Our dataset from the Norwegian context is longitudinal, consisting of ten audio-recorded pre-test genetic counseling sessions. It involves one extended family with a high burden of colorectal cancer. Through theme-oriented discourse analysis, we demonstrate how diagnostic uncertainties give rise to tensions concerning risks and benefits of knowing in both professional and familial spheres, which then map onto accounts of various role responsibilities. For instance, in looking for certainty via advanced genomic testing to reduce diagnostic uncertainty for clients, genetic counselors are confronted with tensions regarding what can be communicated and made known because of their role responsibilities toward what may be regarded as scientific others and clinical others. Likewise, clients are faced with tensions concerning wanting to know/not know, which invokes various familial others and may align or not align with genetic counselors' preferences, especially relating to management of diagnostic uncertainties and secondary findings.

An AICD-based functional screen to identify APP metabolism regulators.

BACKGROUND: A central event in Alzheimer's disease (AD) is the regulated intramembraneous proteolysis of the beta-amyloid precursor protein (APP), to generate the beta-amyloid (Abeta) peptide and the APP intracellular domain (AICD). Abeta is the major component of amyloid plaques and AICD displays transcriptional activation properties. We have taken advantage of AICD transactivation properties to develop a genetic screen to identify regulators of APP metabolism. This screen relies on an APP-Gal4 fusion protein, which upon normal proteolysis, produces AICD-Gal4. Production of AICD-Gal4 induces Gal4-UAS driven luciferase expression. Therefore, when regulators of APP metabolism are modulated, luciferase expression is altered. RESULTS: To validate this experimental approach we modulated alpha-, beta-, and gamma-secretase levels and activities. Changes in AICD-Gal4 levels as measured by Western blot analysis were strongly and significantly correlated to the observed changes in AICD-Gal4 mediated luciferase activity. To determine if a known regulator of APP trafficking/maturation and Presenilin1 endoproteolysis could be detected using the AICD-Gal4 mediated luciferase assay, we knocked-down Ubiquilin 1 and observed decreased luciferase activity. We confirmed that Ubiquilin 1 modulated AICD-Gal4 levels by Western blot analysis and also observed that Ubiquilin 1 modulated total APP levels, the ratio of mature to immature APP, as well as PS1 endoproteolysis. CONCLUSION: Taken together, we have shown that this screen can identify known APP metabolism regulators that control proteolysis, intracellular trafficking, maturation and levels of APP and its proteolytic products. We demonstrate for the first time that Ubiquilin 1 regulates APP metabolism in the human neuroblastoma cell line, SH-SY5Y.