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Sample GSM1098241

Query DataSets for GSM1098241

Status

Public on Apr 01, 2013

Title

METSIM1619

Sample type

SRA

Source name

adipose tissue

Organism

Homo sapiens

Characteristics

age: 60
tissue: adipose tissue
log10 body mass index: 1.375963588
log10 basal metabolic rate (kcal): 1791
log2 estimated glomerular filtration rate using modification of diet in renal disease (egfr_mdrd): 6.291799537
log10 estimated creatinine clearance rate using cockfcrot-gault formulaa (egcr): 6.502500249
plasma free fatty acids under the curve ogtt (mmol/l * min): 17.4
fat mass (%): 19.6
log10 plasma glucose area under the curve (ogtt) (mmol/l * min): 9.796850795
plasma glucose area under the curve above basal (ogtt) (mmol/l * min): 181.5
log10 homair (insulin resistance index based on homa): 0.108865574
log10 homais (insulin secretion index based on homa): 1.611014834
log10 insulin area under the curve (ogtt) (pmol/l * min): 4.432375938
insgenin (insulinogenic index): 1.899573413
log10 insulin area under the curve above basal (ogtt) (pmol/l * min): 4.371714203
log10 matsuda insulin sensitivity index: 0.860605238
muscle mass (%): 47
lg10 serum c-reactive protein (mg/l): 0.116939647
lg10 plasma adiponectin (mg/l): 0.963787827
ogtt fasting plasma free fatty acid (mmol/l): 0.38
ogtt 30 min plasma free fatty acid (mmol/l): 0.18
ogtt 120 min plasma free fatty acid (mmol/l): 0.02
ogtt fasting plasma glucose (mmol/l): 5.9
ogtt 30 min plasma glucose (mmol/l): 9
ogtt 120 min plasma glucose (mmol/l): 5.8
log10 il1 receptor antagonist (pg/ml): 2.498834149
log10 il1 beta (pg/ml): -0.397940009
log10 ogtt fasting plasma insulin (mu/l): 0.69019608
ogtt 30 min plasma insulin (mu/l): 1.661812686
ogtt 120 min plasma insulin (mu/l): 1.572871602
log10 ogtt fasting plasma proinsulin (pm/l): 1.033423755
ogtt 30 min plasma proinsulin (pm/l): 1.376576957
ogtt 120 min plasma proinsulin (pm/l): 1.655138435
log10 bioimpedance: Resistance: 2.717670503
log10 bioimpedance (reactance): 1.770852012
waist to hip ratio: 0.912621359
log10 serum bilirubin (umol/l): 1.591064607
log10 serum alanine aminotransfrase (u/l): 1.322219295
log10 creatinine (umol/l): 1.959041392
log10 total cholesterol (mmol/l): 0.692846919
log10 ldl cholesterol (mmol/l): 0.411619706
log10 hdl cholesterol (mmol/l): 0.209515015
log10 total triglycerides (mmol/l): 0.096910013
log10 serum apoa1 (g/l): 0.161368002
log10 serum apob (g/l): -0.086186148
log10 urinary albumin excretion rate (ug/min): 0.61196828

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