PMID- 37573486
OWN - NLM
STAT- MEDLINE
DCOM- 20231122
LR  - 20240206
IS  - 1098-2272 (Electronic)
IS  - 0741-0395 (Print)
IS  - 0741-0395 (Linking)
VI  - 47
IP  - 8
DP  - 2023 Dec
TI  - Inference of causal metabolite networks in the presence of invalid instrumental 
      variables with GWAS summary data.
PG  - 585-599
LID - 10.1002/gepi.22535 [doi]
AB  - We propose structural equation models (SEMs) as a general framework to infer 
      causal networks for metabolites and other complex traits. Traditionally SEMs are 
      used only for individual-level data under the assumption that all instrumental 
      variables (IVs) are valid. To overcome these limitations, we propose both one- 
      and two-sample approaches for causal network inference based on SEMs that can: 
      (1) perform causal analysis and discover causal relationships among multiple 
      traits; (2) account for the possible presence of some invalid IVs; (3) allow for 
      data analysis using only genome-wide association studies (GWAS) summary 
      statistics when individual-level data are not available; (4) consider the 
      possibility of bidirectional relationships between traits. Our method employs a 
      simple stepwise selection to identify invalid IVs, thus avoiding false positives 
      while possibly increasing true discoveries based on two-stage least squares 
      (2SLS). We use both real GWAS data and simulated data to demonstrate the superior 
      performance of our method over the standard 2SLS/SEMs. For real data analysis, 
      our proposed approach is applied to a human blood metabolite GWAS summary data 
      set to uncover putative causal relationships among the metabolites; we also 
      identify some metabolites (putative) causal to Alzheimer's disease (AD), which, 
      along with the inferred causal metabolite network, suggest some possible pathways 
      of metabolites involved in AD.
CI  - (c) 2023 The Authors. Genetic Epidemiology published by Wiley Periodicals LLC.
FAU - Chen, Siyi
AU  - Chen S
AUID- ORCID: 0000-0001-8019-8149
AD  - Division of Biostatistics, School of Public Health, University of Minnesota, 
      Minneapolis, Minnesota, USA.
FAU - Lin, Zhaotong
AU  - Lin Z
AUID- ORCID: 0000-0001-8723-4392
AD  - Division of Biostatistics, School of Public Health, University of Minnesota, 
      Minneapolis, Minnesota, USA.
FAU - Shen, Xiaotong
AU  - Shen X
AD  - School of Statistics, University of Minnesota, Minneapolis, Minnesota, USA.
FAU - Li, Ling
AU  - Li L
AD  - Department of Experimental and Clinical Pharmacology, College of Pharmacy, 
      University of Minnesota, Minneapolis, Minnesota, USA.
FAU - Pan, Wei
AU  - Pan W
AUID- ORCID: 0000-0002-1159-0582
AD  - Division of Biostatistics, School of Public Health, University of Minnesota, 
      Minneapolis, Minnesota, USA.
LA  - eng
GR  - AG067924/GF/NIH HHS/United States
GR  - U01 AG073079/AG/NIA NIH HHS/United States
GR  - R01 AG074858/AG/NIA NIH HHS/United States
GR  - AG074858/GF/NIH HHS/United States
GR  - AG073079/GF/NIH HHS/United States
GR  - RF1 AG067924/AG/NIA NIH HHS/United States
GR  - AG065636/GF/NIH HHS/United States
GR  - R01 AG065636/AG/NIA NIH HHS/United States
PT  - Journal Article
DEP - 20230813
PL  - United States
TA  - Genet Epidemiol
JT  - Genetic epidemiology
JID - 8411723
SB  - IM
MH  - Humans
MH  - *Genome-Wide Association Study/methods
MH  - Models, Genetic
MH  - Phenotype
MH  - *Alzheimer Disease/genetics
PMC - PMC10840616
MID - NIHMS1923375
OTO - NOTNLM
OT  - Alzheimer's disease
OT  - metabolomics
OT  - stepwise selection
OT  - structural equation modeling
OT  - two-stage least squares
EDAT- 2023/08/13 11:41
MHDA- 2023/11/22 06:43
PMCR- 2024/12/01
CRDT- 2023/08/13 05:26
PHST- 2023/06/19 00:00 [revised]
PHST- 2022/10/24 00:00 [received]
PHST- 2023/08/01 00:00 [accepted]
PHST- 2024/12/01 00:00 [pmc-release]
PHST- 2023/11/22 06:43 [medline]
PHST- 2023/08/13 11:41 [pubmed]
PHST- 2023/08/13 05:26 [entrez]
AID - 10.1002/gepi.22535 [doi]
PST - ppublish
SO  - Genet Epidemiol. 2023 Dec;47(8):585-599. doi: 10.1002/gepi.22535. Epub 2023 Aug 
      13.