Use of complementary and alternative medicine in cancer patients: a European survey

Background: The aim of this study was to explore the use of complementary and alternative medicine (CAM) in cancer patients across a number of European countries. Methods: A descriptive survey design was developed. Fourteen countries participated in the study and data was collected through a descriptive questionnaire from 956 patients. Results: Data suggest that CAM is popular among cancer patients with 35.9% using some form of CAM (range among countries 14.8% to 73.1%). A heterogeneous group of 58 therapies were identified as being used. Herbal medicines and remedies were the most commonly used CAM therapies, together with homeopathy, vitamins/minerals, medicinal teas, spiritual therapies and relaxation techniques. Herbal medicine use tripled from use before diagnosis to use since diagnosis with cancer. Multivariate analysis suggested that the profile of the CAM user was that of younger people, female and with higher educational level. The source of information was mainly from friends/family and the media, while physicians and nurses played a small part in providing CAM-related information. The majority used CAM to increase the body's ability to fight cancer or improve physical and emotional well-being, and many seemed to have benefited from using CAM (even though the benefits were not necessarily related to the initial reason for using CAM). Some 4.4% of patients, however, reported side-effects, mostly transient. Conclusions: It is imperative that health professionals explore the use of CAM with their cancer patients, educate them about potentially beneficial therapies in light of the limited available evidence of effectiveness, and work towards an integrated model of health-care provisio

A Genome-Scale DNA Repair RNAi Screen Identifies SPG48 as a Novel Gene Associated with Hereditary Spastic Paraplegia

We have identified a novel gene in a genome-wide, double-strand break DNA repair RNAi screen and show that is involved in the neurological disease hereditary spastic paraplegia

Identification of circulating proteins associated with general cognitive function among middle-aged and older adults

Identifying circulating proteins associated with cognitive function may point to biomarkers and molecular process of cognitive impairment. Few studies have investigated the association between circulating proteins and cognitive function. We identify 246 protein measures quantified by the SomaScan assay as associated with cognitive function (p < 4.9E-5, n up to 7289). Of these, 45 were replicated using SomaScan data, and three were replicated using Olink data at Bonferroni-corrected significance. Enrichment analysis linked the proteins associated with general cognitive function to cell signaling pathways and synapse architecture. Mendelian randomization analysis implicated higher levels of NECTIN2, a protein mediating viral entry into neuronal cells, with higher Alzheimer’s disease (AD) risk (p = 2.5E-26). Levels of 14 other protein measures were implicated as consequences of AD susceptibility (p < 2.0E-4). Proteins implicated as causes or consequences of AD susceptibility may provide new insight into the potential relationship between immunity and AD susceptibility as well as potential therapeutic targets

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study

The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired β cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study

The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired β cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments

Comprehensive Genomic Analysis of a BRCA2 Deficient Human Pancreatic Cancer

Capan-1 is a well-characterised BRCA2-deficient human cell line isolated from a liver metastasis of a pancreatic adenocarcinoma. Here we report a genome-wide assessment of structural variations and high-depth exome characterization of single nucleotide variants and small insertion/deletions in Capan-1. To identify potential somatic and tumour-associated variations in the absence of a matched-normal cell line, we devised a novel method based on the analysis of HapMap samples. We demonstrate that Capan-1 has one of the most rearranged genomes sequenced to date. Furthermore, small insertions and deletions are detected more frequently in the context of short sequence repeats than in other genomes. We also identify a number of novel mutations that may represent genetic changes that have contributed to tumour progression. These data provide insight into the genomic effects of loss of BRCA2 function

Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug-omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug-drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities. [Abstract copyright: © 2023. The Author(s).