the query terms are
((obesity[Disease]) NOT type 2 diabetes mellitus[Disease]) NOT cardiovascular diseases[Disease]
19 Matching Annotations
- Jul 2017
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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BMI
Test if this shows up in another list.
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Finally found its BMI distribution... turns out to be in demographic category. So most samples from this study have BMI > 24. Good for us.
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dknet.org dknet.org
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Anti-GPCR Obesity Anti-GPCR Obesity Sample pack , Unconjugated antibody
Annotation of query results.
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flybase.org flybase.org
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loss of function allele
https://hyp.is/HC71BHKSEeeUiwOclXegcg/www.cell.com/cell/pdf/0092-8674(94)90507-X.pdf
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www.cell.com www.cell.com
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Partial loss-of-func- tion alleles cause the preferential loss of ventral structures and the expansion of remaining lateral and dorsal struc- tures (Figure 1 c) (Anderson and Niisslein-Volhard, 1988). These loss-of-function mutations in spz produce the same phenotypes as maternal effect mutations in the 10 other genes of the dorsal group.
This paper has been curated by Flybase.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Obesity rs8043757 intron FTO 16 : 53,779,538 5.000 x 10-110 NHGRI 23563607
The top match SNP with key words: Obesity, T2D and CVD is on gene FTO.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Obesity was highly prevalent among the study sample; 64.6% of females and 41.2% of males were obese according to Polynesian cutoffs (BMI ≥ 32 kg/m2). Females were less likely than males to have hypertension (31.7% vs. 36.7%) but equally likely to have diabetes (17.8% vs. 16.4%).
Those with obesity but not hypertension or diabetes can be our candidates.
The data set can be found here: dbGaP Study Accession: phs000972.v2.p1 https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000972.v2.p1
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commonfund.nih.gov commonfund.nih.gov
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‘Metabolically Healthy Obese’
I found some TOPMed and GTEx studies have candidate samples that match this criterion: more specifically, obese but without T2D or CVD history, from dbGAP. I have annotated those studies with tag "data commons examples" as this one.
Here are links to the studies:
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www.informatics.jax.org www.informatics.jax.org
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Chr16:53779880 (GRCm38)
The closest one we can get for human SNP
https://www.ncbi.nlm.nih.gov/snp/?term=rs8043757 https://hyp.is/PoigiHIyEee93tfb1TCdLA/www.ncbi.nlm.nih.gov/gap/phegeni
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Can be a good one, too.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Mostly without CVD.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Mostly without T2D... good.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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This T2D study measured BMI, DBP, SBP and cardiovascular disease medications as well. May have samples we need.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Not good.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Samoans have been studied for >40 years with a focus on the increase in, and levels of, BMI, obesity, and associated cardiometabolic conditions due to economic modernization
This one may contain the sample we need. need to check their publications.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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((obesity[Disease]) NOT type 2 diabetes mellitus[Disease]) NOT cardiovascular diseases[Disease] AND 1[s_discriminator]
NCBI can save this query for me... I can annotate this as well.
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