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Sample GSM1098198

Query DataSets for GSM1098198

Status

Public on Apr 01, 2013

Title

METSIM482

Sample type

SRA

Source name

adipose tissue

Organism

Homo sapiens

Characteristics

age: 50
tissue: adipose tissue
log10 body mass index: 1.403499536
log10 basal metabolic rate (kcal): 1650
log2 estimated glomerular filtration rate using modification of diet in renal disease (egfr_mdrd): 6.623318869
log10 estimated creatinine clearance rate using cockfcrot-gault formulaa (egcr): 6.887438141
plasma free fatty acids under the curve ogtt (mmol/l * min): 15.75
fat mass (%): 21.1
log10 plasma glucose area under the curve (ogtt) (mmol/l * min): 9.63481105
plasma glucose area under the curve above basal (ogtt) (mmol/l * min): 135
log10 homair (insulin resistance index based on homa): 0.361308025
log10 homais (insulin secretion index based on homa): 1.973127854
log10 insulin area under the curve (ogtt) (pmol/l * min): 4.70981249
insgenin (insulinogenic index): 2.36361198
log10 insulin area under the curve above basal (ogtt) (pmol/l * min): 4.648320972
log10 matsuda insulin sensitivity index: 0.62415725
muscle mass (%): 45.1
lg10 serum c-reactive protein (mg/l): -0.122628654
lg10 plasma adiponectin (mg/l): 1.1430148
ogtt fasting plasma free fatty acid (mmol/l): 0.25
ogtt 30 min plasma free fatty acid (mmol/l): 0.17
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): 7.9
ogtt 120 min plasma glucose (mmol/l): 5.3
log10 il1 receptor antagonist (pg/ml): 2.276714495
log10 il1 beta (pg/ml): -0.698970004
log10 ogtt fasting plasma insulin (mu/l): 0.973127854
ogtt 30 min plasma insulin (mu/l): 2.007747778
ogtt 120 min plasma insulin (mu/l): 1.707570176
log10 ogtt fasting plasma proinsulin (pm/l): 1.113943352
ogtt 30 min plasma proinsulin (pm/l): 1.436162647
ogtt 120 min plasma proinsulin (pm/l): 1.525044807
log10 bioimpedance: Resistance: 2.717670503
log10 bioimpedance (reactance): 1.755874856
waist to hip ratio: 0.96969697
log10 serum bilirubin (umol/l): NA
log10 serum alanine aminotransfrase (u/l): 1.62324929
log10 creatinine (umol/l): 1.886490725
log10 total cholesterol (mmol/l): 0.804820679
log10 ldl cholesterol (mmol/l): 0.667452953
log10 hdl cholesterol (mmol/l): 0.164352856
log10 total triglycerides (mmol/l): 0.269512944
log10 serum apoa1 (g/l): 0.204119983
log10 serum apob (g/l): 0.167317335
log10 urinary albumin excretion rate (ug/min): 0.810417027

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