Meta-analysis of human genome-microbiome association studies: The MiBioGen consortium initiative

Background: In recent years, human microbiota, especially gut microbiota, have emerged as an important yet complex trait influencing human metabolism, immunology, and diseases. Many studies are investigating the forces underlying the observed variation, including the human genetic variants that shape human microbiota. Several preliminary genome-wide association studies (GWAS) have been completed, but more are necessary to achieve a fuller picture. Results: Here, we announce the MiBioGen consortium initiative, which has assembled 18 population-level cohorts and some 19,000 participants. Its aim is to generate new knowledge for the rapidly developing field of microbiota research. Each cohort has surveyed the gut microbiome via 16S rRNA sequencing and genotyped their participants with full-genome SNP arrays. We have standardized the analytical pipelines for both the microbiota phenotypes and genotypes, and all the data have been processed using identical approaches. Our analysis of microbiome composition shows that we can reduce the potential artifacts introduced by technical differences in generating microbiota data. We are now in the process of benchmarking the association tests and performing meta-analyses of genome-wide associations. All pipeline and summary statistics results will be shared using public data repositories. Conclusion: We present the largest consortium to date devoted to microbiota-GWAS. We have adapted our analytical pipelines to suit multi-cohort analyses and expect to gain insight into host-microbiota cross-talk at the genome-wide level. And, as an open consortium, we invite more cohorts to join us (by contacting one of the corresponding authors) and to follow the analytical pipeline we have developed

Genome-wide association meta-analysis identifies five novel loci for age-related hearing impairment

Previous research has shown that genes play a substantial role in determining a person's susceptibility to age-related hearing impairment. The existing studies on this subject have different results, which may be caused by difficulties in determining the phenotype or the limited number of participants involved. Here, we have gathered the largest sample to date (discovery n = 9,675; replication n = 10,963; validation n = 356,141), and examined phenotypes that represented low/mid and high frequency hearing loss on the pure tone audiogram. We identified 7 loci that were either replicated and/or validated, of which 5 loci are novel in hearing. Especially the ILDR1 gene is a high profile candidate, as it contains our top SNP, is a known hearing loss gene, has been linked to age-related hearing impairment before, and in addition is preferentially expressed within hair cells of the inner ear. By verifying all previously published SNPs, we can present a paper that combines all new and existing findings to date, giving a complete overview of the genetic architecture of age-related hearing impairment. This is of importance as age-related hearing impairment is highly prevalent in our ageing society and represents a large socio-economic burden