Trillions of microorganisms inhabit the human gut and are regarded as potential key factors for health. Characteristics such as diet, lifestyle, or genetics can shape the composition of the gut microbiota and are usually shared by individuals from comparable ethnic origin. So far, most studies assessing how ethnicity relates to the intestinal microbiota compared small groups living at separate geographical locations. Using fecal 16S ribosomal RNA gene sequencing in 2,084 participants of the Healthy Life in an Urban Setting (HELIUS) study, we show that individuals living in the same city tend to share similar gut microbiota characteristics with others of their ethnic background. Ethnicity contributed to explain the interindividual dissimilarities in gut microbiota composition, with three main poles primarily characterized by operational taxonomic units (OTUs) classified as Prevotella (Moroccans, Turks, Ghanaians), Bacteroides (African Surinamese, South-Asian Surinamese), and Clostridiales (Dutch). The Dutch exhibited the greatest gut microbiota α-diversity and the South-Asian Surinamese the smallest, with corresponding enrichment or depletion in numerous OTUs. Ethnic differences in α-diversity and interindividual dissimilarities were independent of metabolic health and only partly explained by ethnic-related characteristics including sociodemographic, lifestyle, or diet factors. Hence, the ethnic origin of individuals may be an important factor to consider in microbiome research and its potential future applications in ethnic-diverse societies.

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Since the discovery of microRNAs (miRNAs), circulating miRNAs have been proposed as biomarkers for disease. Consequently, many groups have tried to identify circulating miRNA biomarkers for various types of diseases including cardiovascular disease and cancer. However, the replicability of these experiments has been disappointingly low. In order to identify circulating miRNA candidate biomarkers, in general, first an unbiased high-throughput screen is performed in which a large number of miRNAs is detected and quantified in the circulation. Because these are costly experiments, many of such studies have been performed using a low number of study subjects (small sample size). Due to lack of power in small sample size experiments, true effects are often missed and many of the detected effects are wrong. Therefore, it is important to have a good estimate of the appropriate sample size for a miRNA high-throughput screen. In this review, we discuss the effects of small sample sizes in high-throughput screens for circulating miRNAs. Using data from a miRNA high-throughput experiment on isolated monocytes, we illustrate that the implementation of power calculations in a high-throughput miRNA discovery experiment will avoid unnecessarily large and expensive experiments, while still having enough power to be able to detect clinically important differences.

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