Topology and redescriptions detect multiple alternative biological pathways from clinical phenotypes.

Biological pathways play a crucial role in the properties of diseases and are important in drug discovery. Identifying the logical relationships among distinctive phenotypic clusters could reveal possible connections to the underlying pathways. However, this process is challenging since clinical phenotypes are often available through unstructured electronic health records. Moreover, in the absence of a standardized questionnaire, there could be bias among physicians toward selecting certain medical terms. In this article, we develop an efficient pipeline to address these challenges and help practitioners to reveal the pathways associated with the disease. We use topological data analysis and redescriptions and propose a pipeline of four phases: (1) pre-processing the clinical notes to extract the salient concepts, (2) constructing a feature space of the patients to characterize the extracted concepts, (3) leveraging the topological properties to distill the available knowledge and visualize the extracted features, and finally, (4) investigating the bias in the clinical notes of the selected features and identify possible pathways. Our experiments on a publicly available dataset of COVID-19 clinical notes testify that our pipeline can indeed extract meaningful pathways.

Signal enrichment with strain-level resolution in metagenomes using topological data analysis.

BACKGROUND: A metagenome is a collection of genomes, usually in a micro-environment, and sequencing a metagenomic sample en masse is a powerful means for investigating the community of the constituent microorganisms. One of the challenges is in distinguishing between similar organisms due to rampant multiple possible assignments of sequencing reads, resulting in false positive identifications. We map the problem to a topological data analysis (TDA) framework that extracts information from the geometric structure of data. Here the structure is defined by multi-way relationships between the sequencing reads using a reference database. RESULTS: Based primarily on the patterns of co-mapping of the reads to multiple organisms in the reference database, we use two models: one a subcomplex of a Barycentric subdivision complex and the other a Cech complex. The Barycentric subcomplex allows a natural mapping of the reads along with their coverage of organisms while the Cech complex takes simply the number of reads into account to map the problem to homology computation. Using simulated genome mixtures we show not just enrichment of signal but also microbe identification with strain-level resolution. CONCLUSIONS: In particular, in the most refractory of cases where alternative algorithms that exploit unique reads (i.e., mapped to unique organisms) fail, we show that the TDA approach continues to show consistent performance. The Cech model that uses less information is equally effective, suggesting that even partial information when augmented with the appropriate structure is quite powerful.

Probable psychiatric disorder in a rural community of West Bengal, India.

PURPOSE: India faces multiple challenges to mitigate a high burden of psychiatric disorders. The risk of developing psychiatric disorder among the rural Indian population is poorly investigated. This study aims to understand the factors associated with probable psychiatric disorder (PPD) among a select rural Indian population. METHODS: Data from the Birbhum population project of the society for health and demographic surveillance, West Bengal, India, were utilized. Cross-sectional data covering a sample of 31,135 respondents (male 15,384 and female 15,751) aged ≥ 16 years were used. The General Health Questionnaire-28 was administered and the responses were computed into three categories: psychological case, psychological caseness, and normal. Bivariate and multivariate ordered logit regression analyses were applied to attain the study objective. RESULTS: Of the total population, 26% of respondents were identified with PPD. People aged ≥ 60 years, females, divorced/separated/widowed individuals, the unemployed and people with no formal education, individuals from the poorest economic group, and people with a history of selling or mortgaging assets towards their healthcare expenditure had a higher prevalence of psychiatric case within their respective group. CONCLUSIONS: A high burden of PPD was estimated in the select rural community. While designing an intervention for measuring and addressing psychiatric disorders, the socioeconomic gradient of PPD could be helpful.

Characterizing redescriptions using persistent homology to isolate genetic pathways contributing to pathogenesis.

BACKGROUND: Complex diseases may have multiple pathways leading to disease. E.g. coronary artery disease evolves from arterial damage to their epithelial layers, but has multiple causal pathways. More challenging, those pathways are highly correlated within metabolic syndrome. The challenge is to identify specific clusters of phenotype characteristics (composite phenotypes) that may reflect these different etiologies. Further, GWAS seeking to identify SNPs satisfying multiple composite phenotype descriptions allows for lower false positive rates at lower α thresholds, allowing for the possibility of reducing false negatives. This may provide a window into the missing heritability problem. METHODS: We identify significant phenotype patterns, and identify fuzzy redescriptions among those patterns using Jaccard distances. Further, we construct Vietoris-Rips complexes from the Jaccard distances and compute the persistent homology associated with those. The patterns comprising these topological features are identified as composite phenotpyes, whose genetic associations are explored with logistic regression applied to pathways and to GWAS. RESULTS: We identified several phenotypes that tended to be dominated by metabolic syndrome descriptions, and which were distinct among the combinations of metabolic syndrome conditions. Among SNPs marking the RAAS complex, various SNPs associated specifically with different groups of composite phenotypes, as well as distinguishing between the composite phenotypes and simple phenotypes. Each of these showed different genetic associations, namely rs6693954, rs762551, rs1378942, and rs1133323. GWAS identified SNPs that associated with composite phenotypes included rs12365545, rs6847235, and rs701319. Eighteen GWAS identified SNPs appeared in combinations supported in composite combinations with greater power than for any individual phenotype. CONCLUSIONS: We do find systematic associations among metabolic syndrome variates that show distinctive genetic association profiles. Further, the systematic characterization involves composite phenotype descriptions that allow for combined power of individual phenotype GWAS tests, yielding more significance for lower individual thresholds, permitting the exploration of SNPs that would otherwise show as false negatives.

Determinants of quality of life in HIV-infected patients receiving highly active antiretroviral treatment at a medical college ART center in Kolkata, India.

Health-related quality of life (QOL) has become a high priority of long-term management of HIV-infected individuals. The newly diagnosed HIV cases were assessed to obtain sociodemographic and clinical findings. Eyesenk Personality Questionnaire (EPQ), World Health Organization Quality of Life Brief (WHOQOL-BREF) for HIV-infected patients, and Beck Depression Inventory (BDI) were used to get data regarding personality traits, QOL, and depression scores. A total of 175 patients were included in the study, 128 (73.1%) men and 47 (26.9%) women. Overall 56% of patients screened positive for depression. Presence of depression and high neuroticism score in the personality profile of HIV-infected patients are significantly associated with poorer QOL. High neuroticism score was a strong predictor of poorer QOL in psychological and spiritual domain. Management of HIV-infected patients therefore needs to address these psychological issues.

Ego functions in relation to stressful life events and indices of psychopathology in paranoid schizophrenia.

This study explored the role of 12 ego functions in relation to Stressful Life Events and three indices of psychopathology, namely, Psychoticism, Anxiety, and Depression among 60 Bengali adult patients suffering from Paranoid Schizophrenia. Adapted versions of Bellak's Ego Function Assessment-M, Eysenck's Personality Questionnaire, Beck Depression Inventory, and the State-Trait Anxiety Inventory were administered to them. Stepwise multiple regression analyses indicated that Object Relation was associated with all three indices. Scores on Reality Testing correlated with those on Psychoticism, Stressful Life Events and scores on Thought Process with Anxiety, and Stressful Life Events, Sense of Reality, and scores on Defensive Functions with Depression. Hierarchical multiple regression analyses indicated that Object Relation also moderated between stressful life events and anxiety.