Evidence map›Paper›PMID 24627127›Full record

ArticleJournal of lipid research2014

Plasma lipidome is independently associated with variability in metabolic syndrome in Mexican American families.

Hemant Kulkarni, Peter J Meikle, Manju Mamtani, Jacquelyn M Weir, Marcio Almeida, Vincent Diego, Juan Manuel Peralta, Christopher K Barlow, Claire Bellis, Thomas D Dyer and 6 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of lipid research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.4field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 14 citations in OpenAlex.

  1. Trial
  2. Lipidomic signatures in Colombian adults with metabolic syndrome.Journal of diabetes and metabolic disorders · 2024
    Article
  3. Article
  4. RareJournal of lipid research · 2019
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 2 institutions in 2 countries.

Hemant KulkarniDepartment of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227.
Peter J Meikle
Manju Mamtani
Jacquelyn M Weir
Marcio Almeida
Vincent Diego
Juan Manuel Peralta
Christopher K Barlow
Claire Bellis
Thomas D Dyer
Laura Almasy
Michael C Mahaney
Anthony G Comuzzie
Harald H H Göring
Joanne E Curran
John Blangero
Baker Heart and Diabetes Institute · AUTexas Biomedical Research Institute · US

Funding

PEDIGREE ANALYSIS OF LIPOPROTEIN PHENOTYPESP01HL045522 · NHLBI · TEXAS BIOMEDICAL RESEARCH INSTITUTE · PI MAHANEY, MICHAEL CHARLES · 1991 to 2012
$27.6M
Quantitative Trait Locus Mapping in Human PedigreesR37MH059490 · NIMH · TEXAS BIOMEDICAL RESEARCH INSTITUTE · PI BLANGERO, JOHN · 2001 to 2010
$6.8M
EXTRAMULAR RESEARCH FACILITIES CONSTRUCTIONC06RR017515 · NCRR · SOUTHWEST FOUNDATION FOR BIOMEDICAL RES · PI SHADE, ROBERT E · 2003 to 2003
$3.1M
High Performance Computing System for Human GenomicsS10RR029392 · NCRR · TEXAS BIOMEDICAL RESEARCH INSTITUTE · PI BLANGERO, JOHN · 2010 to 2010
$2.1M
Identification of Regulatory Variants in Novel Candidate Genes for DiabetesR01DK079169 · NIDDK · TEXAS BIOMEDICAL RESEARCH INSTITUTE · PI CURRAN, JOANNE E. · 2007 to 2011
$1.7M
Expression-Based Empirical Candidate Genes Influencing Body Mass IndexR01DK082610 · NIDDK · TEXAS BIOMEDICAL RESEARCH INSTITUTE · PI CURRAN, JOANNE E. · 2009 to 2010
$1.7M
Metabolomic studies into the pathogenesis and risk assessment of type 2 diabetesR01DK088972 · NIDDK · BAKER HEART RESEARCH INSTITUTE · PI BLANGERO, JOHN, HAVIV, IZHAK · 2010 to 2012
$905k
MOLECULAR AND BIOCHEMICAL GENETICS LABORATORY RENOVATIONC06RR013556 · NCRR · SOUTHWEST FOUNDATION FOR BIOMEDICAL RES · PI SHADE, ROBERT E · 1998 to 1998
–
NCRR NIH HHS C06 RR013556NCRR NIH HHS C06 RR017515NCRR NIH HHS S10 RR029392NHLBI NIH HHS P01 HL045522NIDDK NIH HHS 1R01DK088972-01NIDDK NIH HHS R01 DK079169NIDDK NIH HHS R01 DK082610NIDDK NIH HHS R01 DK088972NIMH NIH HHS R37 MH059490
6 · The paper itself

Abstract

Plasma lipidome is now increasingly recognized as a potentially important marker of chronic diseases, but the exact extent of its contribution to the interindividual phenotypic variability in family studies is unknown. Here, we used the rich data from the ongoing San Antonio Family Heart Study (SAFHS) and developed a novel statistical approach to quantify the independent and additive value of the plasma lipidome in explaining metabolic syndrome (MS) variability in Mexican American families recruited in the SAFHS. Our analytical approach included two preprocessing steps: principal components analysis of the high-resolution plasma lipidomics data and construction of a subject-subject lipidomic similarity matrix. We then used the Sequential Oligogenic Linkage Analysis Routines software to model the complex family relationships, lipidomic similarities, and other important covariates in a variance components framework. Our results suggested that even after accounting for the shared genetic influences, indicators of lipemic status (total serum cholesterol, TGs, and HDL cholesterol), and obesity, the plasma lipidome independently explained 22% of variability in the homeostatic model of assessment-insulin resistance trait and 16% to 22% variability in glucose, insulin, and waist circumference. Our results demonstrate that plasma lipidomic studies can additively contribute to an understanding of the interindividual variability in MS.

Indexed as

Computational BiologyPedigreeAdultFemaleHumansLipidsMaleMetabolic SyndromeMexican AmericansPhenotypePrincipal Component AnalysisLipidsgeneticsinsulin resistancelipidomicslipidsobesityplasma lipidomicsvariance components

Identifiers

PMID24627127
PMCPMC3995471
OpenAlexW2139326264

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.