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Status |
Public on Apr 01, 2013 |
Title |
METSIM2338 |
Sample type |
SRA |
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Source name |
adipose tissue
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Organism |
Homo sapiens |
Characteristics |
age: 48 tissue: adipose tissue log10 body mass index: 1.431687673 log10 basal metabolic rate (kcal): 1817 log2 estimated glomerular filtration rate using modification of diet in renal disease (egfr_mdrd): 6.592582972 log10 estimated creatinine clearance rate using cockfcrot-gault formulaa (egcr): 7.093259407 plasma free fatty acids under the curve ogtt (mmol/l * min): 14.55 fat mass (%): 23.4 log10 plasma glucose area under the curve (ogtt) (mmol/l * min): 9.764871591 plasma glucose area under the curve above basal (ogtt) (mmol/l * min): 174 log10 homair (insulin resistance index based on homa): 0.471943316 log10 homais (insulin secretion index based on homa): 2 log10 insulin area under the curve (ogtt) (pmol/l * min): 4.615865919 insgenin (insulinogenic index): 2.180535471 log10 insulin area under the curve above basal (ogtt) (pmol/l * min): 4.518671836 log10 matsuda insulin sensitivity index: 0.605773602 muscle mass (%): 44.4 lg10 serum c-reactive protein (mg/l): -0.387216143 lg10 plasma adiponectin (mg/l): 0.73239376 ogtt fasting plasma free fatty acid (mmol/l): 0.25 ogtt 30 min plasma free fatty acid (mmol/l): 0.12 ogtt 120 min plasma free fatty acid (mmol/l): 0.08 ogtt fasting plasma glucose (mmol/l): 5.8 ogtt 30 min plasma glucose (mmol/l): 9.3 ogtt 120 min plasma glucose (mmol/l): 5 log10 il1 receptor antagonist (pg/ml): 2.382539323 log10 il1 beta (pg/ml): -0.886056648 log10 ogtt fasting plasma insulin (mu/l): 1.06069784 ogtt 30 min plasma insulin (mu/l): 1.999565488 ogtt 120 min plasma insulin (mu/l): 1.201397124 log10 ogtt fasting plasma proinsulin (pm/l): 1.136720567 ogtt 30 min plasma proinsulin (pm/l): 1.618048097 ogtt 120 min plasma proinsulin (pm/l): 1.501059262 log10 bioimpedance: Resistance: 2.701567985 log10 bioimpedance (reactance): 1.755874856 waist to hip ratio: 0.927927928 log10 serum bilirubin (umol/l): 1.255272505 log10 serum alanine aminotransfrase (u/l): 1.806179974 log10 creatinine (umol/l): 1.897627091 log10 total cholesterol (mmol/l): 0.758154622 log10 ldl cholesterol (mmol/l): 0.607455023 log10 hdl cholesterol (mmol/l): 0.075546961 log10 total triglycerides (mmol/l): 0.149219113 log10 serum apoa1 (g/l): 0.117271296 log10 serum apob (g/l): 0.093421685 log10 urinary albumin excretion rate (ug/min): -0.114284109
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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.
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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)
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Library strategy |
RNA-Seq |
Library source |
transcriptomic |
Library selection |
size fractionation |
Instrument model |
Illumina HiSeq 2000 |
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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
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Submission date |
Mar 14, 2013 |
Last update date |
May 15, 2019 |
Contact name |
Mete Civelek |
E-mail(s) |
mcivelek@mednet.ucla.edu
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Phone |
310-825-1595
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Fax |
310-794-7345
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Organization name |
University of California Los Angeles
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Department |
Medicine
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Street address |
675 Charles E. Young Dr. S. MRL 3220
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City |
Los Angeles |
State/province |
CA |
ZIP/Postal code |
90066 |
Country |
USA |
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Platform ID |
GPL11154 |
Series (1) |
GSE45159 |
Genetic regulation of human adipose microRNA expression and its consequences for metabolic traits |
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Relations |
SRA |
SRX249174 |
BioSample |
SAMN01978102 |
Supplementary data files not provided |
SRA Run Selector |
Raw data are available in SRA |
Processed data are available on Series record |
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