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Status |
Public on Apr 01, 2013 |
Title |
METSIM6675 |
Sample type |
SRA |
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Source name |
adipose tissue
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Organism |
Homo sapiens |
Characteristics |
age: 46 tissue: adipose tissue log10 body mass index: 1.425726864 log10 basal metabolic rate (kcal): 1645 log2 estimated glomerular filtration rate using modification of diet in renal disease (egfr_mdrd): 6.50287596 log10 estimated creatinine clearance rate using cockfcrot-gault formulaa (egcr): 6.64814536 plasma free fatty acids under the curve ogtt (mmol/l * min): 7.8 fat mass (%): 17.2 log10 plasma glucose area under the curve (ogtt) (mmol/l * min): 9.35645197 plasma glucose area under the curve above basal (ogtt) (mmol/l * min): -64.5 log10 homair (insulin resistance index based on homa): -0.082669574 log10 homais (insulin secretion index based on homa): 1.394451681 log10 insulin area under the curve (ogtt) (pmol/l * min): 4.190527787 insgenin (insulinogenic index): 2.403977964 log10 insulin area under the curve above basal (ogtt) (pmol/l * min): 4.12303453 log10 matsuda insulin sensitivity index: 1.144027476 muscle mass (%): 50.3 lg10 serum c-reactive protein (mg/l): -0.485452247 lg10 plasma adiponectin (mg/l): 0.886490725 ogtt fasting plasma free fatty acid (mmol/l): 0.18 ogtt 30 min plasma free fatty acid (mmol/l): 0.07 ogtt 120 min plasma free fatty acid (mmol/l): 0.02 ogtt fasting plasma glucose (mmol/l): 6 ogtt 30 min plasma glucose (mmol/l): 6.8 ogtt 120 min plasma glucose (mmol/l): 3.5 log10 il1 receptor antagonist (pg/ml): 2.199535781 log10 il1 beta (pg/ml): -1.045757491 log10 ogtt fasting plasma insulin (mu/l): 0.491361694 ogtt 30 min plasma insulin (mu/l): 1.567026366 ogtt 120 min plasma insulin (mu/l): 0.857332496 log10 ogtt fasting plasma proinsulin (pm/l): 1.146128036 ogtt 30 min plasma proinsulin (pm/l): 1.383815366 ogtt 120 min plasma proinsulin (pm/l): 1.357934847 log10 bioimpedance: Resistance: 2.631443769 log10 bioimpedance (reactance): 1.763427994 waist to hip ratio: 0.974226804 log10 serum bilirubin (umol/l): 1 log10 serum alanine aminotransfrase (u/l): 1.176091259 log10 creatinine (umol/l): 1.924279286 log10 total cholesterol (mmol/l): 0.720159303 log10 ldl cholesterol (mmol/l): 0.521138084 log10 hdl cholesterol (mmol/l): 0.260071388 log10 total triglycerides (mmol/l): -0.13667714 log10 serum apoa1 (g/l): 0.193124598 log10 serum apob (g/l): -0.017728767 log10 urinary albumin excretion rate (ug/min): 0.990739639
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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 |
SRX249252 |
BioSample |
SAMN01978180 |
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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