PMID- 37745394
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20240428
DP  - 2023 Sep 12
TI  - A biobank-scale test of marginal epistasis reveals genome-wide signals of 
      polygenic epistasis.
LID - 2023.09.10.557084 [pii]
LID - 10.1101/2023.09.10.557084 [doi]
AB  - The contribution of epistasis (interactions among genes or genetic variants) to 
      human complex trait variation remains poorly understood. Methods that aim to 
      explicitly identify pairs of genetic variants, usually single nucleotide 
      polymorphisms (SNPs), associated with a trait suffer from low power due to the 
      large number of hypotheses tested while also having to deal with the 
      computational problem of searching over a potentially large number of candidate 
      pairs. An alternate approach involves testing whether a single SNP modulates 
      variation in a trait against a polygenic background. While overcoming the 
      limitation of low power, such tests of polygenic or marginal epistasis (ME) are 
      infeasible on Biobank-scale data where hundreds of thousands of individuals are 
      genotyped over millions of SNPs. We present a method to test for ME of a SNP on a 
      trait that is applicable to biobank-scale data. We performed extensive 
      simulations to show that our method provides calibrated tests of ME. We applied 
      our method to test for ME at SNPs that are associated with 53 quantitative traits 
      across  approximately  300 K unrelated white British individuals in the UK Biobank (UKBB). 
      Testing 15, 601 trait-loci associations that were significant in GWAS, we 
      identified 16 trait-loci pairs across 12 traits that demonstrate strong evidence 
      of ME signals (p-value p < 5/10). We further partitioned the significant ME 
      signals across the genome to identify 6 trait-loci pairs with evidence of local 
      (within-chromosome) ME while 15 show evidence of distal (cross-chromosome) ME. 
      Across the 16 trait-loci pairs, we document that the proportion of trait variance 
      explained by ME is about 12x as large as that explained by the GWAS effects on 
      average (range: 0.59 to 43.89). Our results show, for the first time, evidence of 
      interaction effects between individual genetic variants and overall polygenic 
      background modulating complex trait variation.
FAU - Fu, Boyang
AU  - Fu B
AD  - Department of Computer Science, UCLA, Los Angeles, CA, USA.
FAU - Pazokitoroudi, Ali
AU  - Pazokitoroudi A
AD  - Department of Computer Science, UCLA, Los Angeles, CA, USA.
FAU - Xue, Albert
AU  - Xue A
AD  - Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA.
FAU - Anand, Aakarsh
AU  - Anand A
AD  - Department of Computer Science, UCLA, Los Angeles, CA, USA.
FAU - Anand, Prateek
AU  - Anand P
AD  - Department of Computer Science, UCLA, Los Angeles, CA, USA.
FAU - Zaitlen, Noah
AU  - Zaitlen N
AD  - Department of Neurology, UCLA, Los Angeles, CA, USA.
AD  - Department of Computational Medicine, David Geffen School of Medicine, UCLA, Los 
      Angeles, CA, USA.
FAU - Sankararaman, Sriram
AU  - Sankararaman S
AD  - Department of Computer Science, UCLA, Los Angeles, CA, USA.
AD  - Department of Computational Medicine, David Geffen School of Medicine, UCLA, Los 
      Angeles, CA, USA.
AD  - Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, 
      CA, USA.
LA  - eng
GR  - U01 MH126798/MH/NIMH NIH HHS/United States
GR  - R01 MH122688/MH/NIMH NIH HHS/United States
GR  - R01 MH130581/MH/NIMH NIH HHS/United States
GR  - R01 HG006399/HG/NHGRI NIH HHS/United States
GR  - T32 HG002536/HG/NHGRI NIH HHS/United States
GR  - R01 GM142112/GM/NIGMS NIH HHS/United States
GR  - R35 GM125055/GM/NIGMS NIH HHS/United States
PT  - Preprint
DEP - 20230912
PL  - United States
TA  - bioRxiv
JT  - bioRxiv : the preprint server for biology
JID - 101680187
PMC - PMC10515811
EDAT- 2023/09/25 06:43
MHDA- 2023/09/25 06:44
PMCR- 2023/09/22
CRDT- 2023/09/25 05:00
PHST- 2023/09/25 06:43 [pubmed]
PHST- 2023/09/25 06:44 [medline]
PHST- 2023/09/25 05:00 [entrez]
PHST- 2023/09/22 00:00 [pmc-release]
AID - 2023.09.10.557084 [pii]
AID - 10.1101/2023.09.10.557084 [doi]
PST - epublish
SO  - bioRxiv [Preprint]. 2023 Sep 12:2023.09.10.557084. doi: 
      10.1101/2023.09.10.557084.