Genome-Wide Search for SNP Interactions in GWAS Data : Algorithm, Feasibility, Replication Using Schizophrenia Datasets

Kwan Yeung LEE; Kwong Sak LEUNG; Suk Ling MA; Hon Cheong SO; Dan HUANG; Nelson Leung Sang TANG; Man Hon WONG

doi:10.3389/fgene.2020.01003

Genome-Wide Search for SNP Interactions in GWAS Data : Algorithm, Feasibility, Replication Using Schizophrenia Datasets

Kwan Yeung LEE^*, Kwong Sak LEUNG, Suk Ling MA, Hon Cheong SO, Dan HUANG, Nelson Leung Sang TANG, Man Hon WONG

^*Corresponding author for this work

Research output: Journal Publications › Journal Article (refereed) › peer-review

13 Citations (Scopus)

Abstract

In this study, we looked for potential gene-gene interaction in susceptibility to schizophrenia by an exhaustive searching for SNP–SNP interactions in 3 GWAS datasets (phs000021:phg000013, phs000021:phg000014, phs000167) using our recently published algorithm. The search space for SNP–SNP interaction was confined to 8 biologically plausible ways of interaction under dominant-dominant or recessive-recessive modes. First, we performed our search of all pair-wise combination of 729,454 SNPs after filtering by SNP genotype quality. All possible pairwise interactions of any 2 SNPs (5 × 10¹¹) were exhausted to search for significant interaction which was defined by p-value of chi-square tests. Nine out the top 10 interactions, protein coding genes were partnered with non-coding RNA (ncRNA) which suggested a new alternative insight into interaction biology other than the frequently sought-after protein–protein interaction. Therefore, we extended to look for replication among the top 10,000 interaction SNP pairs and high proportion of concurrent genes forming the interaction pairs were found. The results indicated that an enrichment of signals over noise was present in the top 10,000 interactions. Then, replications of SNP–SNP interaction were confirmed for 14 SNPs-pairs in both replication datasets. Biological insight was highlighted by a potential binding between FHIT (protein coding gene) and LINC00969 (lncRNA) which showed a replicable interaction between their SNPs. Both of them were reported to have expression in brain. Our study represented an early attempt of exhaustive interaction analysis of GWAS data which also yield replicated interaction and new insight into understanding of genetic interaction in schizophrenia.

Original language	English
Article number	1003
Number of pages	14
Journal	Frontiers in Genetics
Volume	11
DOIs	https://doi.org/10.3389/fgene.2020.01003
Publication status	Published - 28 Aug 2020
Externally published	Yes

Bibliographical note

Funding Information:
Datasets phs000021:phg000013, phs000021:phg000014, and phs000167 used for the analyses described in this manuscript were downloaded from the database of Genotypes and Phenotypes (dbGaP) at http://www.ncbi.nlm.nih.gov/gap through dbGaP accession numbers phs000021.v3.p2 and phs000167.v1.p1. Datasets phs000021:phg000013 and phs000021:phg000014 are both originated from the study titled Genome-Wide Association of Schizophrenia Study (dbGaP accession number: phs000021.v3.p2). Samples and associated phenotype data of this study were provided by the Molecular Genetics of Schizophrenia Collaboration (PI: Pablo V. Gejman, Evanston Northwestern Healthcare (ENH) and Northwestern University, Evanston, IL, United States) and the genotyping of samples of this study was provided through the Genetic Association Information Network (GAIN). Data collection of this study was supported by the funding from the National Institute of Mental Health (R01 MH67257, R01 MH59588, R01 MH59571, R01 MH59565, R01 MH59587, R01 MH60870, R01 MH59566, R01 MH59586, R01 MH61675, R01 MH60879, R01 MH81800, U01 MH46276, U01 MH46289U01 MH46318, U01 MH79469, and U01 MH79470). Dataset phs000167 is originated from the study titled Molecular Genetics of Schizophrenia ? nonGAIN Sample (MGS_nonGAIN) (dbGaP accession number: phs000167.v1.p1). Data collection of this study was supported by the funding from Genomics Research Branch at NIMH. Samples and associated phenotype data of this study were collected under the following grants: NIMH Schizophrenia Genetics Initiative U01s: MH46276 (C. R. Cloninger), MH46289 (C. Kaufmann), and MH46318 (M. T. Tsuang); and MGS Part 1 (MGS1) and Part 2 (MGS2) R01s: MH67257 (N. G. Buccola), MH59588 (B. J. Mowry), MH59571 (P. V. Gejman), MH59565 (Robert Freedman), MH59587 (F. Amin), MH60870 (W. F. Byerley), MH59566 (D. W. Black), MH59586 (J. M. Silverman), MH61675 (D. F. Levinson), and MH60879 (C. R. Cloninger). The genotyping of samples of this study was provided through the Genetic Association Information Network (GAIN) and under the MGS U01s: MH79469 and MH79470. Further details of collection sites, individuals, and institutions may be found in data supplement Table 1 of Sanders et al. (2008) and at the study dbGaP pages. Funding. NT is currently receiving VC Discretionary Fund of CUHK for other research projects. SM was supported by a CUHK direct grant. This project is also partially supported by direct grant of CUHK.

Publisher Copyright:
© Copyright © 2020 Lee, Leung, Ma, So, Huang, Tang and Wong.

Keywords

exhaustive search
gene–lncRNA interactions
GWAS
schizophrenia
second order SNP–SNP interaction

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10.3389/fgene.2020.01003

Cite this

@article{9583f6f614a14d5bb870764c819ca420,

title = "Genome-Wide Search for SNP Interactions in GWAS Data : Algorithm, Feasibility, Replication Using Schizophrenia Datasets",

abstract = "In this study, we looked for potential gene-gene interaction in susceptibility to schizophrenia by an exhaustive searching for SNP–SNP interactions in 3 GWAS datasets (phs000021:phg000013, phs000021:phg000014, phs000167) using our recently published algorithm. The search space for SNP–SNP interaction was confined to 8 biologically plausible ways of interaction under dominant-dominant or recessive-recessive modes. First, we performed our search of all pair-wise combination of 729,454 SNPs after filtering by SNP genotype quality. All possible pairwise interactions of any 2 SNPs (5 × 1011) were exhausted to search for significant interaction which was defined by p-value of chi-square tests. Nine out the top 10 interactions, protein coding genes were partnered with non-coding RNA (ncRNA) which suggested a new alternative insight into interaction biology other than the frequently sought-after protein–protein interaction. Therefore, we extended to look for replication among the top 10,000 interaction SNP pairs and high proportion of concurrent genes forming the interaction pairs were found. The results indicated that an enrichment of signals over noise was present in the top 10,000 interactions. Then, replications of SNP–SNP interaction were confirmed for 14 SNPs-pairs in both replication datasets. Biological insight was highlighted by a potential binding between FHIT (protein coding gene) and LINC00969 (lncRNA) which showed a replicable interaction between their SNPs. Both of them were reported to have expression in brain. Our study represented an early attempt of exhaustive interaction analysis of GWAS data which also yield replicated interaction and new insight into understanding of genetic interaction in schizophrenia.",

keywords = "exhaustive search, gene–lncRNA interactions, GWAS, schizophrenia, second order SNP–SNP interaction",

author = "LEE, {Kwan Yeung} and LEUNG, {Kwong Sak} and MA, {Suk Ling} and SO, {Hon Cheong} and Dan HUANG and TANG, {Nelson Leung Sang} and WONG, {Man Hon}",

note = "Funding Information: Datasets phs000021:phg000013, phs000021:phg000014, and phs000167 used for the analyses described in this manuscript were downloaded from the database of Genotypes and Phenotypes (dbGaP) at http://www.ncbi.nlm.nih.gov/gap through dbGaP accession numbers phs000021.v3.p2 and phs000167.v1.p1. Datasets phs000021:phg000013 and phs000021:phg000014 are both originated from the study titled Genome-Wide Association of Schizophrenia Study (dbGaP accession number: phs000021.v3.p2). Samples and associated phenotype data of this study were provided by the Molecular Genetics of Schizophrenia Collaboration (PI: Pablo V. Gejman, Evanston Northwestern Healthcare (ENH) and Northwestern University, Evanston, IL, United States) and the genotyping of samples of this study was provided through the Genetic Association Information Network (GAIN). Data collection of this study was supported by the funding from the National Institute of Mental Health (R01 MH67257, R01 MH59588, R01 MH59571, R01 MH59565, R01 MH59587, R01 MH60870, R01 MH59566, R01 MH59586, R01 MH61675, R01 MH60879, R01 MH81800, U01 MH46276, U01 MH46289U01 MH46318, U01 MH79469, and U01 MH79470). Dataset phs000167 is originated from the study titled Molecular Genetics of Schizophrenia ? nonGAIN Sample (MGS_nonGAIN) (dbGaP accession number: phs000167.v1.p1). Data collection of this study was supported by the funding from Genomics Research Branch at NIMH. Samples and associated phenotype data of this study were collected under the following grants: NIMH Schizophrenia Genetics Initiative U01s: MH46276 (C. R. Cloninger), MH46289 (C. Kaufmann), and MH46318 (M. T. Tsuang); and MGS Part 1 (MGS1) and Part 2 (MGS2) R01s: MH67257 (N. G. Buccola), MH59588 (B. J. Mowry), MH59571 (P. V. Gejman), MH59565 (Robert Freedman), MH59587 (F. Amin), MH60870 (W. F. Byerley), MH59566 (D. W. Black), MH59586 (J. M. Silverman), MH61675 (D. F. Levinson), and MH60879 (C. R. Cloninger). The genotyping of samples of this study was provided through the Genetic Association Information Network (GAIN) and under the MGS U01s: MH79469 and MH79470. Further details of collection sites, individuals, and institutions may be found in data supplement Table 1 of Sanders et al. (2008) and at the study dbGaP pages. Funding. NT is currently receiving VC Discretionary Fund of CUHK for other research projects. SM was supported by a CUHK direct grant. This project is also partially supported by direct grant of CUHK. Publisher Copyright: {\textcopyright} Copyright {\textcopyright} 2020 Lee, Leung, Ma, So, Huang, Tang and Wong.",

year = "2020",

month = aug,

day = "28",

doi = "10.3389/fgene.2020.01003",

language = "English",

volume = "11",

journal = "Frontiers in Genetics",

issn = "1664-8021",

publisher = "Frontiers Media S.A.",

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T1 - Genome-Wide Search for SNP Interactions in GWAS Data : Algorithm, Feasibility, Replication Using Schizophrenia Datasets

AU - LEE, Kwan Yeung

AU - LEUNG, Kwong Sak

AU - MA, Suk Ling

AU - SO, Hon Cheong

AU - HUANG, Dan

AU - TANG, Nelson Leung Sang

AU - WONG, Man Hon

N1 - Funding Information: Datasets phs000021:phg000013, phs000021:phg000014, and phs000167 used for the analyses described in this manuscript were downloaded from the database of Genotypes and Phenotypes (dbGaP) at http://www.ncbi.nlm.nih.gov/gap through dbGaP accession numbers phs000021.v3.p2 and phs000167.v1.p1. Datasets phs000021:phg000013 and phs000021:phg000014 are both originated from the study titled Genome-Wide Association of Schizophrenia Study (dbGaP accession number: phs000021.v3.p2). Samples and associated phenotype data of this study were provided by the Molecular Genetics of Schizophrenia Collaboration (PI: Pablo V. Gejman, Evanston Northwestern Healthcare (ENH) and Northwestern University, Evanston, IL, United States) and the genotyping of samples of this study was provided through the Genetic Association Information Network (GAIN). Data collection of this study was supported by the funding from the National Institute of Mental Health (R01 MH67257, R01 MH59588, R01 MH59571, R01 MH59565, R01 MH59587, R01 MH60870, R01 MH59566, R01 MH59586, R01 MH61675, R01 MH60879, R01 MH81800, U01 MH46276, U01 MH46289U01 MH46318, U01 MH79469, and U01 MH79470). Dataset phs000167 is originated from the study titled Molecular Genetics of Schizophrenia ? nonGAIN Sample (MGS_nonGAIN) (dbGaP accession number: phs000167.v1.p1). Data collection of this study was supported by the funding from Genomics Research Branch at NIMH. Samples and associated phenotype data of this study were collected under the following grants: NIMH Schizophrenia Genetics Initiative U01s: MH46276 (C. R. Cloninger), MH46289 (C. Kaufmann), and MH46318 (M. T. Tsuang); and MGS Part 1 (MGS1) and Part 2 (MGS2) R01s: MH67257 (N. G. Buccola), MH59588 (B. J. Mowry), MH59571 (P. V. Gejman), MH59565 (Robert Freedman), MH59587 (F. Amin), MH60870 (W. F. Byerley), MH59566 (D. W. Black), MH59586 (J. M. Silverman), MH61675 (D. F. Levinson), and MH60879 (C. R. Cloninger). The genotyping of samples of this study was provided through the Genetic Association Information Network (GAIN) and under the MGS U01s: MH79469 and MH79470. Further details of collection sites, individuals, and institutions may be found in data supplement Table 1 of Sanders et al. (2008) and at the study dbGaP pages. Funding. NT is currently receiving VC Discretionary Fund of CUHK for other research projects. SM was supported by a CUHK direct grant. This project is also partially supported by direct grant of CUHK. Publisher Copyright: © Copyright © 2020 Lee, Leung, Ma, So, Huang, Tang and Wong.

PY - 2020/8/28

Y1 - 2020/8/28

N2 - In this study, we looked for potential gene-gene interaction in susceptibility to schizophrenia by an exhaustive searching for SNP–SNP interactions in 3 GWAS datasets (phs000021:phg000013, phs000021:phg000014, phs000167) using our recently published algorithm. The search space for SNP–SNP interaction was confined to 8 biologically plausible ways of interaction under dominant-dominant or recessive-recessive modes. First, we performed our search of all pair-wise combination of 729,454 SNPs after filtering by SNP genotype quality. All possible pairwise interactions of any 2 SNPs (5 × 1011) were exhausted to search for significant interaction which was defined by p-value of chi-square tests. Nine out the top 10 interactions, protein coding genes were partnered with non-coding RNA (ncRNA) which suggested a new alternative insight into interaction biology other than the frequently sought-after protein–protein interaction. Therefore, we extended to look for replication among the top 10,000 interaction SNP pairs and high proportion of concurrent genes forming the interaction pairs were found. The results indicated that an enrichment of signals over noise was present in the top 10,000 interactions. Then, replications of SNP–SNP interaction were confirmed for 14 SNPs-pairs in both replication datasets. Biological insight was highlighted by a potential binding between FHIT (protein coding gene) and LINC00969 (lncRNA) which showed a replicable interaction between their SNPs. Both of them were reported to have expression in brain. Our study represented an early attempt of exhaustive interaction analysis of GWAS data which also yield replicated interaction and new insight into understanding of genetic interaction in schizophrenia.

AB - In this study, we looked for potential gene-gene interaction in susceptibility to schizophrenia by an exhaustive searching for SNP–SNP interactions in 3 GWAS datasets (phs000021:phg000013, phs000021:phg000014, phs000167) using our recently published algorithm. The search space for SNP–SNP interaction was confined to 8 biologically plausible ways of interaction under dominant-dominant or recessive-recessive modes. First, we performed our search of all pair-wise combination of 729,454 SNPs after filtering by SNP genotype quality. All possible pairwise interactions of any 2 SNPs (5 × 1011) were exhausted to search for significant interaction which was defined by p-value of chi-square tests. Nine out the top 10 interactions, protein coding genes were partnered with non-coding RNA (ncRNA) which suggested a new alternative insight into interaction biology other than the frequently sought-after protein–protein interaction. Therefore, we extended to look for replication among the top 10,000 interaction SNP pairs and high proportion of concurrent genes forming the interaction pairs were found. The results indicated that an enrichment of signals over noise was present in the top 10,000 interactions. Then, replications of SNP–SNP interaction were confirmed for 14 SNPs-pairs in both replication datasets. Biological insight was highlighted by a potential binding between FHIT (protein coding gene) and LINC00969 (lncRNA) which showed a replicable interaction between their SNPs. Both of them were reported to have expression in brain. Our study represented an early attempt of exhaustive interaction analysis of GWAS data which also yield replicated interaction and new insight into understanding of genetic interaction in schizophrenia.

KW - exhaustive search

KW - gene–lncRNA interactions

KW - GWAS

KW - schizophrenia

KW - second order SNP–SNP interaction

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U2 - 10.3389/fgene.2020.01003

DO - 10.3389/fgene.2020.01003

M3 - Journal Article (refereed)

C2 - 33133133

AN - SCOPUS:85091220302

SN - 1664-8021

VL - 11

JO - Frontiers in Genetics

JF - Frontiers in Genetics

M1 - 1003

ER -

Genome-Wide Search for SNP Interactions in GWAS Data : Algorithm, Feasibility, Replication Using Schizophrenia Datasets

Abstract

Bibliographical note

Keywords

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