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. 2022 Oct;18(10):1846-1867.
doi: 10.1002/alz.12507. Epub 2021 Dec 17.

Whole genome sequencing-based copy number variations reveal novel pathways and targets in Alzheimer's disease

Chen Ming  1   2   3 , Minghui Wang  1   2   3 , Qian Wang  1   2   3 , Ryan Neff  1   2   3 , Erming Wang  1   2   3 , Qi Shen  1   2   3 , Joseph S Reddy  4 , Xue Wang  4 , Mariet Allen  5 , Nilüfer Ertekin-Taner  5   6 , Philip L De Jager  7   8 , David A Bennett  9 , Vahram Haroutunian  10   11   12   13 , Eric Schadt  1   2 , Bin Zhang  1   2   3
Affiliations

Whole genome sequencing-based copy number variations reveal novel pathways and targets in Alzheimer's disease

Chen Ming et al. Alzheimers Dement. 2022 Oct.

Abstract

Introduction: A few copy number variations (CNVs) have been reported for Alzheimer's disease (AD). However, there is a lack of a systematic investigation of CNVs in AD based on whole genome sequencing (WGS) data.

Methods: We used four methods to identify consensus CNVs from the WGS data of 1,411 individuals and further investigated their functional roles in AD using the matched transcriptomic and clinicopathological data.

Results: We identified 3,012 rare AD-specific CNVs whose residing genes are enriched for cellular glucuronidation and neuron projection pathways. Genes whose mRNA expressions are significantly correlated with common CNVs are involved in major histocompatibility complex class II receptor activity. Integration of CNVs, gene expression, and clinical and pathological traits further pinpoints a key CNV that potentially regulates immune response in AD.

Discussion: We identify CNVs as potential genetic regulators of immune response in AD. The identified CNVs and their downstream gene networks reveal novel pathways and targets for AD.

Keywords: Alzheimer's disease; copy number variation; correlation network; immune response; late-onset Alzheimer's disease; multi-omics integration; regulation of response to external stimulus; whole genomic sequencing.

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Conflict of interest statement

Chen Ming, Minghui Wang, Qian Wang, Ryan Neff, Erming Wang, Qi Shen, Joseph S. Reddy, and Xue Wang have nothing to disclose. Bin Zhang, Mariet Allen, David A. Bennett, Vahram Haroutunian, and Eric Schadt received support for the present manuscript. Specifically, this manuscript was supported by Bin Zhang‘s NIH/NIA grants (R01AG046170, RF1AG054014, RF1AG057440, R01AG057907, U01AG052411, R01AG062355, U01AG058635, R01AG068030) and Mariet Allen's grant (U01‐AG046139) as well as NIH grants for David A. Bennett, Vahram Haroutunian, and Eric Schadt. In the past 36 months, Bin Zhang, Minghui Wang, Mariet Allen, Nilüfer Ertekin‐Taner, Philip L. De Jager, David A. Bennett, Vahram Haroutunian, and Eric Schadt received grants from NIH or foundations. Specifically, Bin Zhang received 21 grants (R01AG046170, RF1AG054014, RF1AG057440, R01AG057907, U01AG052411, R01AG062355, U01AG058635, R01AG068030, R01AG062661, R01AG062355, HHS‐NIH‐NIAID‐BAA2018, R01 MH111679, R01DA043247, R01DK118243, R01DA048279, R56AG058655, R01AG063819, R01D029322, R01DA047880, R01AG062661, R01AG060341, R21AI149013). Mariet Allen received 3 grants (U01‐AG046139, R01‐AG061796, U01‐AG046139, RF1‐AG51504). Nilüfer Ertekin‐Taner received 7 grants (U01AG046139, RF1AG051504, R01AG061796, P30AG062677, U01AG061359, NHLBI75N92019D00031/75N92019F00125, R01AG050603). Minghui Wang received one grant (1RF1AG066526‐01A1). Philip L. De Jager, David A. Bennett, Vahram Haroutunian, and Eric Schadt received NIH grants. David A. Bennett received a grant from NIH Neurovision. Eric Schadt also received grants from the Helmsley Foundation. None of the co‐authors received royalties or licenses in the past 36 months. In the past 36 months, Philip L. De Jager received consultant fees from Partech, Roche, and Biogen; David A. Bennett received consultant fees from AbbVie, DSMB, Takeda, Origent, and SBIR; Vahram Haroutunian received a consultant fee of $350 from Synaptec; and Eric Schadt is paid by Berg Pharmaceuticals for participation on their scientific advisory board. In the past 36 months, Bin Zhang received an honorarium for presentation from Lehigh University; Nilüfer Ertekin‐Taner received payments for her presentations at the 15th International Symposium on Geriatrics and Gerontology Inflammation and Dementia: Genomics, System and Therapeutics, Nagoya, Japan; Philip L. De Jager received payments from Novartis, Astra Zeneca, and Biogen for lectures/presentations; David A. Bennett received payments or honoraria from academia in US and government (NGO) for lectures/presentations. In the past 36 months, Bin Zhang received support from FNIH to attend the AMP‐AD program meeting at NIH (the payment was made to him); Minghui Wang received support from FNIH for his travel and hotel lodging for attending NIH project meetings (the payments were made to him); Mariet Allen received a travel fellowship from Alzheimer's Association International Conference for conference registration but without payments, travel reimbursement from Alzheimer's Association, and travel reimbursement from NIH (the payments were made to her); Nilüfer Ertekin‐Taner received supports for attending the following conferences: 11th ISABS Conference (Split, Croatia), the 15th International Symposium on Geriatrics and Gerontology Inflammation and Dementia: Genomics, System and Therapeutics (Nagoya, Japan), multiple NIH meetings, Department of Neurology, Indiana University School of Medicine (Bloomington, Indiana); David A. Bennett received support for attending meetings from academia in US and government (NGO). In the past 36 months, the following authors have pending patents: Bin Zhang (US2020/056080 titled “STATHMIN 2 (STMN2) as a therapeutic target for Parkinson's disease,” MS‐0029‐01‐US‐P titled “A Novel therapeutic strategy for targeting the molecular subtypes of AD,” and MS‐00‐30‐01‐US‐P titled “Novel Compounds for Treating Alzheimer's Disease”), Minghui Wang (US2020/056080 titled “STATHMIN 2 (STMN2) as a therapeutic target for Parkinson's disease”), Ryan Neff (MS‐0029‐01‐US‐P titled “A Novel therapeutic strategy for targeting the molecular subtypes of AD”). Eric Schadt has patents under consideration relating to novel drug targets and targeting mechanisms for AD, patent applications filed and under review for biomarkers relating to various forms of cancer, predicting drug response and matching to therapies. In the past 36 months, Eric Schadt was on the board of directors for Sema4, a for‐profit company, and for Sage Bionetworks and 4YouAndMe, both non‐profit research institutions; Nilüfer Ertekin‐Taner was on the external advisory board for the NIH TREAT‐AD consortium; David A. Bennett was on the external advisory board of AbbVie.

David A. Bennett received equipment, materials, drugs, medical writing, gifts, or other services from Rush philanthropy in the past 36 months. The authors declare that they have no other competing interests.

Figures

FIGURE 1
FIGURE 1
Genomic copy number variation (CNV) distribution in the two cohorts (MSBB and ROSMAP). Track 0: Human genome cytoband. Track 1: Deletions in ROSMAP. Track 2: Duplications in the ROSMAP. Track 3: multi‐allelic CNVs in ROSMAP. Track 4: Alzheimer's disease (AD)‐specific CNVs in the ROSMAP. Track 5: Deletions in MSBB. Track 6: Duplications in MSBB. Track 7: multi‐allelic CNVs in MSBB. Track 8: AD‐specific CNVs in MSBB. Orange and blue lines represent deletion and duplication, respectively. Green lines represent multi‐allelic CNVs
FIGURE 2
FIGURE 2
Overall features of the copy number variations (CNVs) identified in MSBB and ROSMAP, including composition of CNV types, site frequency spectrum (SFS). (A) Pie chart of the CNV composition in each cohort. The exact numbers can be found in Table 1. (B) CNV sharing pattern across the two cohorts. The exact numbers can be found in Table S7. The CNV proportion in each category is based on the boundary of each cohort separately. The overlapping criteria is defined as the reciprocal overlap ratio larger than 0.5. (C) SFS of deletions and duplications in the MSBB and ROSMAP cohorts
FIGURE 3
FIGURE 3
Comparison of the copy number variation (CNV) sets in three clinical diagnostic groups (normal (NL), mild cognitive impairment (MCI), and AD) in MSBB and ROSMAP. (A) Intersection of the CNV sets in three different diagnostic groups in each cohort. The numbers are defined by comparing different diagnostic groups in the same cohort. (B) Illustration of the concept of group‐specific CNVs. The pink, orange, and green shadow regions represent the AD‐specific, MCI‐specific, and NL‐specific CNV sets. All the samples in the two cohorts are considered here. (C) Intersection of the diagnostic group‐specific CNV sets in MSBB and ROSMAP. The numbers are based on the cross‐cohort comparison. (D) Site frequency spectrum of AD‐specific deletions and duplications. DEL and DUP represent deletion and duplication, respectively
FIGURE 4
FIGURE 4
Functional analysis of Alzheimer's disease (AD)‐, mild cognitive impairment (MCI)‐, and normal (NL)‐specific copy number variation (CNV) genes. CNV genes are the genes whose genomic locations overlap with a given CNV. (A) AD‐specific CNV genes are enriched for cellular glucuronidation, neuron projection, uronic acid metabolic process, extrinsic component of plasma membrane, synapse, catenin complex, and multicellular organismal signaling. (B) Genes whose genomic locations overlap with multiple AD‐specific CNVs are enriched for neuron development, neuron recognition, neuron differentiation, cell projection organization, neurogenesis, axon, and neuron projection. (C) MCI‐specific CNV genes are enriched for ligase activity forming carbon‐sulfur bonds. (D) NL‐specific CNV genes are enriched for immunoglobulin complex. (E) Circos plot of the 64 conserved AD‐specific CNVs in JJ Peters VA Medical Center Brain Bank and Religious Orders Study/Memory and Aging Project. The outer track 1 represents the genomic locations of the 64 conserved AD‐specific CNVs, while the outer track 2 represents the genes whose genomic locations overlap these 64 CNVs. The inner track 1 represents the genomic location of the APP duplication region. (F) The 29 AD‐specific CNVs encompassing the APP duplication region illustrated in the University of California Santa Cruz genome browser track. The light blue shade represents the location of the APP gene
FIGURE 4
FIGURE 4
Functional analysis of Alzheimer's disease (AD)‐, mild cognitive impairment (MCI)‐, and normal (NL)‐specific copy number variation (CNV) genes. CNV genes are the genes whose genomic locations overlap with a given CNV. (A) AD‐specific CNV genes are enriched for cellular glucuronidation, neuron projection, uronic acid metabolic process, extrinsic component of plasma membrane, synapse, catenin complex, and multicellular organismal signaling. (B) Genes whose genomic locations overlap with multiple AD‐specific CNVs are enriched for neuron development, neuron recognition, neuron differentiation, cell projection organization, neurogenesis, axon, and neuron projection. (C) MCI‐specific CNV genes are enriched for ligase activity forming carbon‐sulfur bonds. (D) NL‐specific CNV genes are enriched for immunoglobulin complex. (E) Circos plot of the 64 conserved AD‐specific CNVs in JJ Peters VA Medical Center Brain Bank and Religious Orders Study/Memory and Aging Project. The outer track 1 represents the genomic locations of the 64 conserved AD‐specific CNVs, while the outer track 2 represents the genes whose genomic locations overlap these 64 CNVs. The inner track 1 represents the genomic location of the APP duplication region. (F) The 29 AD‐specific CNVs encompassing the APP duplication region illustrated in the University of California Santa Cruz genome browser track. The light blue shade represents the location of the APP gene
FIGURE 5
FIGURE 5
Functional analysis of copy number variation (CNV)‐correlated genes. (A) Pathways enriched in the CNV‐correlated genes in five different brain regions of AD cases. (B) Pathways enriched in the CNV‐correlated genes in the Alzheimer's disease (AD), mild cognitive impairment (MCI), and normal (NL) groups in the Religious Orders Study/Memory and Aging Project
FIGURE 6
FIGURE 6
Correlation analysis of two copy number variations (CNVs; i.e., DEL6593 and mCNV6614), HLA‐DRB5 gene expression, and Alzheimer's disease (AD) traits. (A) Illustration of the genomic location of the two CNVs, that is, DEL6593 and mCNV6614 in JJ Peters VA Medical Center Brain Bank (MSBB). The counterpart of DEL6593 is DEL21513 in Religious Orders Study/Memory and Aging Project (ROSMAP). The counterpart of mCNV6614 is mCNV21541 in ROSMAP. The light blue shade represents the location of the HLA‐DRB5 gene. (B‐F) Correlation between copy number dosage of the sequence in the DEL6593 locus and the expression level of HLA‐DRB5 in different brain regions. (G‐K) Correlation between copy number dosage of the sequence in the mCNV6614 locus and the expression level of HLA‐DRB5 in different brain regions. x = 0 means the individuals carry homologous deletions in this locus, while x = 1 means the individuals carry heterozygous deletion. x = 2 means the individuals have two copies of the sequence, suggesting no deletion. x = 3 means the individuals carry three copies of the sequence, which is heterozygous duplication. (L) Differential expression of HLA‐DRB5 based on the Plaque Mean group in the BM‐36 region. (M) The expression of HLA‐DRB5 is positively correlated with the Consortium to Establish a Registry for Alzheimer's Disease score in the BM‐36 region
FIGURE 7
FIGURE 7
Integrative network analysis of matched copy number variation (CNV), gene expression, and trait data in the JJ Peters VA Medical Center Brain Bank (MSBB) and the Religious Orders Study/Memory and Aging Project (ROSMAP). A network comprised of CNV‐gene, CNV‐trait, and gene‐trait pairs with significant correlations is constructed from each cohort and is termed as a CNV‐gene‐trait correlation network. All CNVs discovered in the two cohorts are considered while constructing the network, including Alzheimer's disease (AD)‐specific CNVs and non‐AD‐specific CNVs. (A) CNV‐gene‐trait correlation network from MSBB. B, CNV‐gene‐trait correlation network from ROSMAP. In both network plots, the orange square, light‐blue circle, and purple triage shape of a node represent CNV, gene, and trait, respectively. The intensity of edge color is proportional to correlation coefficient, while red and blue colors represent positive and negative correlations, respectively. Blue and red labels represent down‐ and upregulated genes, respectively. Known AD genome‐wide association study genes are marked with a star symbol. The detailed correlation matrix is shown in Tables S26‐S27.
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