PMID- 30275876
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20230928
IS  - 1753-6561 (Print)
IS  - 1753-6561 (Electronic)
IS  - 1753-6561 (Linking)
VI  - 12
IP  - Suppl 9
DP  - 2018
TI  - Application of Bayesian networks to GAW20 genetic and blood lipid data.
PG  - 19
LID - 10.1186/s12919-018-0116-y [doi]
LID - 19
AB  - BACKGROUND: Bayesian networks have been proposed as a way to identify possible 
      causal relationships between measured variables based on their conditional 
      dependencies and independencies. We explored the use of Bayesian network analyses 
      applied to the GAW20 data to identify possible causal relationships between 
      differential methylation of cytosine-phosphate-guanine dinucleotides (CpGs), 
      single-nucleotide polymorphisms (SNPs), and blood lipid trait (triglycerides 
      [TGs]). METHODS: After initial exploratory linear regression analyses, 2 Bayesian 
      networks analyses were performed. First, we used the real data and modeled the 
      effects of 4 CpGs previously found to be associated with TGs in the Genetics of 
      Lipid Lowering Drugs and Diet Network Study (GOLDN). Second, we used the 
      simulated data and modeled the effect of a fictional lipid modifying drug with 5 
      known causal SNPs and 5 corresponding CpGs. RESULTS: In the real data we show 
      that relationships are present between the CpGs, TGs, and other variables-age, 
      sex, and center. In the simulated data, we show, using linear regression, that no 
      CpGs and only 1 SNP were associated with a change in TG levels, and, using 
      Bayesian network analysis, that relationships are present between the change in 
      TG levels and most SNPs, but not with CpGs. CONCLUSIONS: Even when the causal 
      relationships between variables are known, as with the simulated data, if the 
      relationships are not strong then it is challenging to reproduce them in a 
      Bayesian network.
FAU - Howey, Richard A J
AU  - Howey RAJ
AD  - Institute of Genetic Medicine, Newcastle University, Central Parkway, Newcastle 
      upon Tyne, NE1 3BZ UK. ISNI: 0000 0001 0462 7212. GRID: grid.1006.7
FAU - Cordell, Heather J
AU  - Cordell HJ
AD  - Institute of Genetic Medicine, Newcastle University, Central Parkway, Newcastle 
      upon Tyne, NE1 3BZ UK. ISNI: 0000 0001 0462 7212. GRID: grid.1006.7
LA  - eng
GR  - R01 HL104135/HL/NHLBI NIH HHS/United States
GR  - R01 HL091357/HL/NHLBI NIH HHS/United States
GR  - R01 GM031575/GM/NIGMS NIH HHS/United States
GR  - U01 HL072524/HL/NHLBI NIH HHS/United States
GR  - WT_/Wellcome Trust/United Kingdom
PT  - Journal Article
DEP - 20180917
PL  - England
TA  - BMC Proc
JT  - BMC proceedings
JID - 101316936
PMC - PMC6157285
COIS- Not applicable.Not applicable.The authors declare that they have no competing 
      interests.Springer Nature remains neutral with regard to jurisdictional claims in 
      published maps and institutional affiliations.
EDAT- 2018/10/03 06:00
MHDA- 2018/10/03 06:01
PMCR- 2018/09/17
CRDT- 2018/10/03 06:00
PHST- 2018/10/03 06:00 [entrez]
PHST- 2018/10/03 06:00 [pubmed]
PHST- 2018/10/03 06:01 [medline]
PHST- 2018/09/17 00:00 [pmc-release]
AID - 116 [pii]
AID - 10.1186/s12919-018-0116-y [doi]
PST - epublish
SO  - BMC Proc. 2018 Sep 17;12(Suppl 9):19. doi: 10.1186/s12919-018-0116-y. eCollection 
      2018.