Journal: Genome medicine
The effects of probiotic supplementation on fecal microbiota composition in healthy adults have not been well established. We aimed to provide a systematic review of the potential evidence for an effect of probiotic supplementation on the composition of human fecal microbiota as assessed by high-throughput molecular approaches in randomized controlled trials (RCTs) of healthy adults.
Emerging evidence suggests that the in utero environment is not sterile as once presumed. Work in the mouse demonstrated transmission of commensal bacteria from mother to fetus during gestation, though it is unclear what modulates this process. We have previously shown in the nonhuman primate that, independent of obesity, a maternal high-fat diet during gestation and lactation persistently shapes the juvenile gut microbiome. We therefore sought to interrogate in a population-based human longitudinal cohort whether a maternal high-fat diet similarly alters the neonatal and infant gut microbiome in early life.
While the cost of whole genome sequencing (WGS) is approaching the realm of routine medical tests, it remains too tardy to help guide the management of many acute medical conditions. Rapid WGS is imperative in light of growing evidence of its utility in acute care, such as in diagnosis of genetic diseases in very ill infants, and genotype-guided choice of chemotherapy at cancer relapse. In such situations, delayed, empiric, or phenotype-based clinical decisions may meet with substantial morbidity or mortality. We previously described a rapid WGS method, STATseq, with a sensitivity of >96 % for nucleotide variants that allowed a provisional diagnosis of a genetic disease in 50 h. Here improvements in sequencing run time, read alignment, and variant calling are described that enable 26-h time to provisional molecular diagnosis with >99.5 % sensitivity and specificity of genotypes. STATseq appears to be an appropriate strategy for acutely ill patients with potentially actionable genetic diseases.
Genomic medicine has paved the way for identifying biomarkers and therapeutically actionable targets for complex diseases, but is complicated by the involvement of thousands of variably expressed genes across multiple cell types. Single-cell RNA-sequencing study (scRNA-seq) allows the characterization of such complex changes in whole organs.
While age and the APOE ε4 allele are major risk factors for Alzheimer’s disease (AD), a small percentage of individuals with these risk factors exhibit AD resilience by living well beyond 75 years of age without any clinical symptoms of cognitive decline.
Personalized therapy provides the best outcome of cancer care and its implementation in the clinic has been greatly facilitated by recent convergence of enormous progress in basic cancer research, rapid advancement of new tumor profiling technologies, and an expanding compendium of targeted cancer therapeutics.
Influenza infects tens of millions of people every year in the USA. Other than notable risk groups, such as children and the elderly, it is difficult to predict what subpopulations are at higher risk of infection. Viral challenge studies, where healthy human volunteers are inoculated with live influenza virus, provide a unique opportunity to study infection susceptibility. Biomarkers predicting influenza susceptibility would be useful for identifying risk groups and designing vaccines.
Expression quantitative trait locus analysis has emerged as an important component of efforts to understand how genetic polymorphisms influence disease risk and is poised to make contributions to translational medicine. Here we review how expression quantitative trait locus analysis is aiding the identification of which gene(s) within regions of association are causal for a disease or phenotypic trait; the narrowing down of the cell types or regulators involved in the etiology of disease; the characterization of drivers and modifiers of cancer; and our understanding of how different environments and cellular contexts can modify gene expression. We also introduce the concept of transcriptional risk scores as a means of refining estimates of individual liability to disease based on targeted profiling of the transcripts that are regulated by polymorphisms jointly associated with disease and gene expression.
Monitoring treatment and early detection of fatal breast cancer (BC) remains a major unmet need. Aberrant circulating DNA methylation (DNAme) patterns are likely to provide a highly specific cancer signal. We hypothesized that cell-free DNAme markers could indicate disseminated breast cancer, even in the presence of substantial quantities of background DNA.
Despite a myriad of attempts in the last three decades to diagnose ovarian cancer (OC) earlier, this clinical aim still remains a significant challenge. Aberrant methylation patterns of linked CpGs analyzed in DNA fragments shed by cancers into the bloodstream (i.e. cell-free DNA) can provide highly specific signals indicating cancer presence.