Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, non-coding variants from which pinpointing causal genes remains challenging. Here, we combined data from 718,734 individuals to discover rare and low-frequency (MAF<5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which eight in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2, ZNF169) newly implicated in human obesity, two (MC4R, KSR2) previously observed in extreme obesity, and two variants in GIPR. Effect sizes of rare variants are ~10 times larger than of common variants, with the largest effect observed in carriers of an MC4R stop-codon (p.Tyr35Ter, MAF=0.01%), weighing ~7kg more than non-carriers. Pathway analyses confirmed enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically-supported therapeutic targets to treat obesity.

Biomarkers have a wide application in research and clinic, they help to choose the correct treatment for diseases. Recent studies, addressing the vaginal microbiome using next generation sequencing (NGS), reported the involvement of bacterial species in infertility. We compared the vaginal microbiome of idiopathic infertile women with that of healthy, including bacterial vaginosis affected women and non-idiopathic infertile women, to identify bacterial species suitable as biomarkers. Information on microorganisms was obtained from the V3-16S rDNA sequencing of cervical-vaginal fluids of 96 women using the Ion Torrent platform. Data were processed with QIIME and classified against the Vaginal 16S rDNA Reference Database. The analysis revealed a significant beta-diversity variation (p < 0.001) between the four groups included in the study. L. iners, L. crispatus, and L. gasseri distinguished idiopathic infertile women from the other groups. In these women, a microbial profile similar to that observed in bacterial vaginosis women has been detected. Our results suggest that the quantitative assessment and identification of specific microorganisms of the cervical-vaginal microflora could increase the accuracy of available tools for the diagnosis of infertility and improve the adoption of therapeutic protocols.

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