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Status |
Public on Apr 01, 2013 |
Title |
METSIM5510 |
Sample type |
SRA |
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Source name |
adipose tissue
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Organism |
Homo sapiens |
Characteristics |
age: 58 tissue: adipose tissue log10 body mass index: 1.518901503 log10 basal metabolic rate (kcal): 1581 log2 estimated glomerular filtration rate using modification of diet in renal disease (egfr_mdrd): 6.454927697 log10 estimated creatinine clearance rate using cockfcrot-gault formulaa (egcr): 6.922418135 plasma free fatty acids under the curve ogtt (mmol/l * min): 22.2 fat mass (%): 27.3 log10 plasma glucose area under the curve (ogtt) (mmol/l * min): 10.12023788 plasma glucose area under the curve above basal (ogtt) (mmol/l * min): 453 log10 homair (insulin resistance index based on homa): 0.29666519 log10 homais (insulin secretion index based on homa): 1.908485019 log10 insulin area under the curve (ogtt) (pmol/l * min): 4.694052108 insgenin (insulinogenic index): 1.782698878 log10 insulin area under the curve above basal (ogtt) (pmol/l * min): 4.639536291 log10 matsuda insulin sensitivity index: 0.576841583 muscle mass (%): 40.1 lg10 serum c-reactive protein (mg/l): -0.18243463 lg10 plasma adiponectin (mg/l): 0.819543936 ogtt fasting plasma free fatty acid (mmol/l): 0.34 ogtt 30 min plasma free fatty acid (mmol/l): 0.27 ogtt 120 min plasma free fatty acid (mmol/l): 0.02 ogtt fasting plasma glucose (mmol/l): 5.5 ogtt 30 min plasma glucose (mmol/l): 9.3 ogtt 120 min plasma glucose (mmol/l): 10.5 log10 il1 receptor antagonist (pg/ml): 2.08174325 log10 il1 beta (pg/ml): -1.045757491 log10 ogtt fasting plasma insulin (mu/l): 0.908485019 ogtt 30 min plasma insulin (mu/l): 1.667452953 ogtt 120 min plasma insulin (mu/l): 2.073351702 log10 ogtt fasting plasma proinsulin (pm/l): 1.269512944 ogtt 30 min plasma proinsulin (pm/l): 1.57054294 ogtt 120 min plasma proinsulin (pm/l): 1.892094603 log10 bioimpedance: Resistance: 2.673020907 log10 bioimpedance (reactance): 1.69019608 waist to hip ratio: 1.004424779 log10 serum bilirubin (umol/l): NA log10 serum alanine aminotransfrase (u/l): 1.462397998 log10 creatinine (umol/l): 1.919078092 log10 total cholesterol (mmol/l): 0.751279104 log10 ldl cholesterol (mmol/l): 0.59439255 log10 hdl cholesterol (mmol/l): 0.139879086 log10 total triglycerides (mmol/l): 0.056904851 log10 serum apoa1 (g/l): 0.120573931 log10 serum apob (g/l): 0.025305865 log10 urinary albumin excretion rate (ug/min): 0.965004339
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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 |
SRX249217 |
BioSample |
SAMN01978145 |
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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