NCBI Logo
GEO Logo
   NCBI > GEO > Accession DisplayHelp Not logged in | LoginHelp
GEO help: Mouse over screen elements for information.
          Go
Sample GSM1098252 Query DataSets for GSM1098252
Status Public on Apr 01, 2013
Title METSIM1777
Sample type SRA
 
Source name adipose tissue
Organism Homo sapiens
Characteristics age: 54
tissue: adipose tissue
log10 body mass index: 1.388478806
log10 basal metabolic rate (kcal): 1431
log2 estimated glomerular filtration rate using modification of diet in renal disease (egfr_mdrd): 6.600779512
log10 estimated creatinine clearance rate using cockfcrot-gault formulaa (egcr): 6.521616776
plasma free fatty acids under the curve ogtt (mmol/l * min): 25.35
fat mass (%): 18.5
log10 plasma glucose area under the curve (ogtt) (mmol/l * min): 9.811374694
plasma glucose area under the curve above basal (ogtt) (mmol/l * min): 238.5
log10 homair (insulin resistance index based on homa): 0.112456041
log10 homais (insulin secretion index based on homa): 1.72427587
log10 insulin area under the curve (ogtt) (pmol/l * min): 4.335898992
insgenin (insulinogenic index): 1.453755036
log10 insulin area under the curve above basal (ogtt) (pmol/l * min): 4.251784177
log10 matsuda insulin sensitivity index: 0.896028713
muscle mass (%): 46.3
lg10 serum c-reactive protein (mg/l): 0.602059991
lg10 plasma adiponectin (mg/l): 0.986771734
ogtt fasting plasma free fatty acid (mmol/l): 0.45
ogtt 30 min plasma free fatty acid (mmol/l): 0.28
ogtt 120 min plasma free fatty acid (mmol/l): 0.04
ogtt fasting plasma glucose (mmol/l): 5.5
ogtt 30 min plasma glucose (mmol/l): 9.7
ogtt 120 min plasma glucose (mmol/l): 5.2
log10 il1 receptor antagonist (pg/ml): 2.282576801
log10 il1 beta (pg/ml): -1.045757491
log10 ogtt fasting plasma insulin (mu/l): 0.72427587
ogtt 30 min plasma insulin (mu/l): 1.401400541
ogtt 120 min plasma insulin (mu/l): 1.652246341
log10 ogtt fasting plasma proinsulin (pm/l): 1.127104798
ogtt 30 min plasma proinsulin (pm/l): 1.328379603
ogtt 120 min plasma proinsulin (pm/l): 1.789580712
log10 bioimpedance: Resistance: 2.728353782
log10 bioimpedance (reactance): 1.785329835
waist to hip ratio: 0.947368421
log10 serum bilirubin (umol/l): 1.176091259
log10 serum alanine aminotransfrase (u/l): 1.414973348
log10 creatinine (umol/l): 1.886490725
log10 total cholesterol (mmol/l): 0.728353782
log10 ldl cholesterol (mmol/l): 0.445604203
log10 hdl cholesterol (mmol/l): 0.359835482
log10 total triglycerides (mmol/l): -0.017728767
log10 serum apoa1 (g/l): 0.267171728
log10 serum apob (g/l): -0.075720714
log10 urinary albumin excretion rate (ug/min): 0.949694882
Treatment protocol We analyzed samples from 200 male human subjects that are part of the METSIM (METabolic Syndrome In Men) study. The population-based cross-sectional METSIM study included 10,197 men, aged from 45 to 73 years, who were randomly selected from the population register of the Kuopio town in eastern Finland (population 95,000). Every participant had a 1-day outpatient visit to the Clinical Research Unit at the University of Kuopio, including an interview on the history of previous diseases and current drug treatment and an evaluation of glucose tolerance and cardiovascular risk factors. After 12 hours of fasting, a 2-h oral 75-g glucose tolerance test was performed and the blood samples were drawn at 0, 30 and 120 min. Plasma glucose was measured by enzymatic hexokinase photometric assay (Konelab Systems reagents; Thermo Fischer Scientific, Vantaa, Finland). Insulin was determined by immunoassay (ADVIA Centaur Insulin IRI no. 02230141; Siemens Medical Solutions Diagnostics, Tarrytown, NY). Height and weight were measured to the nearest 0.5 cm and 0.1 kg, respectively. Waist (at the midpoint between the lateral iliac crest and lowest rib) and hip circumference (at the level of the trochanter major) were measured to the nearest 0.5 cm. Body composition was determined by bioelectrical impedance (RJL Systems) in subjects in the supine position after a 12-hour fast.
Extracted molecule total RNA
Extraction protocol Abdominal subcutaneous adipose tissue was obtained with needle biopsies. Total RNA was isolated from the adipose tissue using Qiagen miRNeasy kit according to manufacturer’s instructions. RNA Integrity Number (RIN) values were assessed with the Agilent Bioanalyzer 2100 instrument. Samples with RIN values greater than 7.0 were used for transcriptional profiling.
Small RNA libraries were prepared using the Illumina TruSeq Small RNA protocol utilizing up to 48 unique index sequences (Illumina Catalog Number FC-102-1009). For two samples (METSIM490 and METSIM6589) we also prepared small RNA libraries using Illumina Small RNA v1.5 sample preparation protocol (Catalog # FC-930-1501)
 
Library strategy RNA-Seq
Library source transcriptomic
Library selection size fractionation
Instrument model Illumina HiSeq 2000
 
Data processing Illumina Casava1.7 software used for basecalling.
Sequencing files were converted to FASTQ format using a custom Perl script. In order to assign the indexed reads to each METSIM subject, a Python script was used to partition the FASTQ file for each lane into multiple FASTQ files, each of which corresponded to one individual. To be included in the partitioned file, a read had to have an exact match to one of the 48 possible index sequences, unambiguously identifying the individual from whom the read originated. Reads which did not exactly match an index sequence were discarded.
The reads were then aligned to the hg19 version of the genome using the Novoalign tool with the following settings: -l16 -t30 -h90 -rA -R 1 -m -g 200 –k. Novoalign software trims the adapter sequences while aligning.
We used the Bioconductor package GenomicRanges for R (v.2.14.0) to count the number of reads with alignment coordinates that overlap the coordinates of known mature miRNAs. Whenever a read mapped to 'x' genomic loci, the read would contribute a count of 1/x to those regions. The genomic coordinates for known mature miRNAs were downloaded from miRBase version 18.
To enable comparison of counts between samples, we normalized the expression values by dividing the counts for a given mature miRNA by the sum of all the miRNA counts for the corresponding individual. For subsequent analysis, we considered the expression levels of 356 miRNAs that had at least 5 reads in half of the study participants.
Genome_build: hg19
Supplementary_files_format_and_content: tab-delimited text files include unnormalized weighted counts for each miRNA
 
Submission date Mar 14, 2013
Last update date May 15, 2019
Contact name Mete Civelek
E-mail(s) mcivelek@mednet.ucla.edu
Phone 310-825-1595
Fax 310-794-7345
Organization name University of California Los Angeles
Department Medicine
Street address 675 Charles E. Young Dr. S. MRL 3220
City Los Angeles
State/province CA
ZIP/Postal code 90066
Country USA
 
Platform ID GPL11154
Series (1)
GSE45159 Genetic regulation of human adipose microRNA expression and its consequences for metabolic traits
Relations
SRA SRX249151
BioSample SAMN01978079

Supplementary data files not provided
SRA Run SelectorHelp
Raw data are available in SRA
Processed data are available on Series record

| NLM | NIH | GEO Help | Disclaimer | Accessibility |
NCBI Home NCBI Search NCBI SiteMap