DOI: 10.5061/dryad.pk0p2ngwg
title: 16S sequencing data of Asian female population with BMD reduction

description: Background: Osteopenia and osteoporosis are both common bone diseases in
 postmenopausal women, but their clinical manifestations tend to be
 unnoticeable until bone loss-induced fractures occur which could endanger
 personal safety and lead to other injuries. This phenomenon makes it
 difficult to identify the population with osteoporosis, leading to failure
 to receive treatment timely. As a significant public health concern, the
 early diagnosis of osteopenia and osteoporosis has become an urgent
 clinical topic. Methods: We conducted metabolomic analysis on plasma
 samples and 16S sequencing on fecal samples from humans. While 142 women
 participated in metabolomic analysis, only 118 of them joined the
 transcriptomics cohort. By statistical methods, we managed to identify
 relevant biomarkers of osteopenia and osteoporosis consisting of
 metabolites and genera and establish early diagnosis models, including
 clinical features, classical indexes and selected biomarkers. The
 efficiency of these models was also validated. Results: Metabolites
 included homo-L-arginine, 3-methylglutarylcarnitine, linoleyl carnitine,
 and estrone glucuronide, and gut microbes included Coprococcus, Dialister,
 Erysipelatoclostridium, Marvinbryantia and Stenotrophomonas were
 identified as biomarkers of osteoporosis while the metabolite
 dihomo-gamma-linolenoylethanolamide and genera including
 Lachnospiraceae_NC2004_group, Lachnospiraceae_NK4A136_group and Roseburia
 were identified as as biomarkers of osteopenia. The area under the curve
 (AUC) of early diagnosis models for distinguishing osteoporosis from
 normal, osteopenia from normal and osteoporosis from osteopenia were 0.95,
 0.77, and 0.92 respectively. Conclusion: We identified biomarkers of both
 osteopenia and osteoporosis consisting of metabolites and gut microbes and
 investigated the mechanisms underlying their influence on the reduction of
 BMD. High-reliability prediction models were built through artificial
 neural networks and random forest and these models can help early
 diagnosis of osteopenia and osteoporosis to realize early intervention and
 early treatment.
description: The fecal samples were collected in sterile plastic cups from
 participants and stored at -80 °C within 1 hour. The microbial DNA was
 extracted by using TIANamp Stool DNA Kit (TIANGEN, Beijing, China) and the
 DNA solution was stored at -20°C. The concentration of the extracted DNA
 was determined by Nanodrop (Spectrophotometer ND1000) for further
 amplification. The forward Illumine adapter sequence was CCTACGGGNGGCWGCAG
 and the reverse was GACTACHVGGGTATCTAATCC. The
 sequencing results were analyzed according to Qiime2 procedure. Illumina
 NovaSeq 6000 was used for acquiring the raw sequencing data and DADA2 was
 applied for filtration and denoising of the raw data which is equivalent
 to clustering DNA sequences with 10% similarity[26].  Only low-quality
 sequences were removed and corrected, and algorithm recognition was used
 to remove chimeras. The redundancy of the denoised sequences was directly
 removed redundancy to obtain features, including OTUs, ASVs, and other
 information. The clear data were acquired from raw data
 by filtration treatment. By deleting reads with low-quality bases of mass
 value data ≤14 exceeding, N bases ³ 10 or overlap between adaptor and
 reads exceeding 10, the filtration result is presented in Figure S2A. The
 sequencing error rate was used to detect abnormal base positions with high
 error rates within the sequencing range (Figure S2B). The quality of the
 sequencing data was mainly distributed above Q30 (≥ 80%) to ensure the
 normal progression of the subsequent analysis. According to the
 characteristics of sequencing technology, the base quality at the end of
 sequencing reads is generally lower than that at the front end.
description: # 16S sequencing data of Asian female population with BMD reduction
 These data files are
 original data of 16S rRNA sequencing among Asian female of normal group,
 osteopenia group and osteoporosis group. These data files are original
 data of 16S rRNA sequencing among Asian females of normal group,
 osteopenia group and osteoporosis group. The files from A1 to A53 belong
 to the osteopenia group, the files from B1 to B36 belong to the
 osteoporosis group and the files from Con1 to Con37 belong to the normal
 group.