Epigenetic and genetic risk of Alzheimer disease from autopsied brains in two ethnic groups
Alzheimer’s disease (AD) is a chronic and progressive neurodegenerative disorder accompanied by cognitive decline that gradually worsens over years. The etiology of AD is complex involving different molecular mechanisms, which may be the result of not only heritable genetic risks but also by factors that act on the epigenome. The advancement in identifying genetic contributions to AD has also piqued interest in epigenetic contributions. The most recent genome-wide association study (GWAS) of AD reported over 70 genetic loci for AD risk . Candidate gene and genome-wide DNA methylation studies have implicated approximately 21 genetic loci with differential methylation levels associated with AD . Loci identified in genetic and epigenetic studies  suggest a common molecular hub that captures causal risk factors for AD. APOE ε4 is most consistently confirmed genetic risk factor for AD and the methylation levels of the CpG island within APOE were found to be lower in AD brains compared to brains from healthy individuals . DNA methylation occurs on the CpG dinucleotides, the single nucleotide polymorphisms altering the creation of the CpG dinucleotides are named CpG-related single nucleotide polymorphism (CGS). We previously found CGSes in the MS4A region have a dose-dependent effect on AD in persons who identified as non-Hispanic White (NHW) . We focused our study on Caribbean Hispanics (CH) because prior studies of genetic associations of AD suggested heterogeneity across racial and ethnic groups . We hypothesize that the CGS may play an important role in the risk of AD and AD pathology in Hispanics by regulating methylation and expression levels. We also investigated whether the findings in CH are unique to the population or can be generalized to other populations including non-Hispanic Whites (NHW). To test this hypothesis, we conducted a systematic analysis based on CGS in participants who identified as CH and were enrolled in Washington Heights-Inwood Columbia Aging Project (WHICAP) or the Estudio Familiar de Influencia Genética en Alzheimer (EFIGA) . We used a genome-wide sliding-window approach to prioritize genetic loci comprised of CGSes associated with the risk of clinical diagnosis of AD in CH. The prioritized loci from the genome-wide analyses were followed by detailed studies to determine their function on brain DNA methylation and mRNA transcription. We analyzed both the cis- and trans-effects of the molecular mechanisms from genetics to DNA methylation and mRNA gene expression in postmortem brain tissue from CH.   Study description Cohorts included for genetic studies We included 7,155 CH from the Washington Heights-Inwood Columbia Aging Project (WHICAP)  and the Estudio Familiar de Influencia Genética en Alzheimer (EFIGA) . The WHICAP study is an ongoing prospective, community-based, multiethnic longitudinal study of Medicare beneficiaries 65 years and older residing in northern Manhattan (Washington Heights, Hamilton Heights, and Inwood). All the participants underwent a comprehensive examination including the assessment of general health and function, standardized physical and neurological examination, and a neuropsychological battery of tests. Follow-up visits were performed every 1.5–2 years, repeating similar examinations. Initiated in 1998, EFIGA recruited individuals of CH ancestry including familial and sporadic AD. The individuals were recruited in New York City using local newspapers, the local CH radio station, and postings throughout the Washington Heights-Inwood neighborhood. AD was defined as any individual meeting NINCDS-ADRDA criteria for probable or possible AD . The severity of dementia was rated according to the Clinical Dementia Rating . We also analyzed 1,283 NHW from the Religious Order Study and the Memory & Aging Project (ROSMAP) study to investigate whether the top loci identified in the CH can be generalized to NHW. ROSMAP recruits older individuals without known dementia and their detailed information of both ante-mortem and postmortem phenotyping were collected . For this study, we have included in total 1,283 NHW with whole-genome sequencing data and clinical diagnosis of AD. Cohorts with brain DNA methylation and RNA sequencing (RNA-seq) New York Brain Bank (NYBB): Tissue from the prefrontal cortex came from The NIA Alzheimer’s disease family-based study (NIA-AD FBS), WHICAP, EFIGA, and NCRAD. The NIA-AD FBS included 9,682 family members, and 1,096 unrelated, nondemented elderly from different race/ethnicity groups from 1,756 families with suspected AD. NCRAD included unaffected individuals from families with a history of AD. A description of the families has been previously detailed in a report . University of California, Davis Alzheimer’s Disease Center (UCD ADC): With the goal to conduct research on diversity and risk of AD dementia, UCD applied an active community outreach approach to recruit the individuals from the communities of Alameda, Contra Costa, Sacramento, San Joaquin, Solano, and Yolo County. The overall percentage of CH individuals 60 years of age and older residing in these counties ranged from 7.1 to 14.3% . Brain frontal cortex was dissected to measure DNA methylation and RNA sequencing. Florida Autopsied Multi-Ethnic (FLAME) cohort: The FLAME cohort is derived from the State of Florida brain bank housed at the Mayo Clinic Florida . The FLAME cohort consists of a total of 2,809 autopsied individuals with a wide range of neurodegenerative diseases, who were self-identified as Hispanic/Latino, black/African, and non-Hispanic white/European. The fixed hemi-brain (typically left hemisphere) was weighed, and the frontal cortex was cut and then placed in 10% formalin solution. The University of Pennsylvania Integrated Neurodegenerative Disease Biobank: Patients with neurodegenerative disease are recruited into the autopsy program by the different clinical cores. The subjects selected for the autopsy were followed in the clinical centers with detailed clinical information and most of them were also collected with biofluid, neuroimaging, and genetic data/samples. The left hemisphere and brain stem were immersed in 10% neutral buffered formalin for 2 weeks, whereas the right hemisphere was sliced coronally and frozen. Brain frontal cortex was dissected to measure DNA methylation and RNA sequencing. University of California, San Diego Alzheimer’s Disease Research Center (UCSD ADC): Postmortem frontal cortex tissue from the center’s longitudinally followed cohort was used for this study. Blocks of tissue were provided from autopsy-verified cases after fixation in 10% formalin for 4 weeks. Cases were selected using detailed clinical, biomarker and demographics information collected at visits. The Religious Order Study and the Memory & Aging Project (ROSMAP): We included 516 NHW who have measurements of both postmortem brain DNA methylation and RNA sequencing (RNA-seq) from postmortem brain tissues from the dorsolateral prefrontal cortex. The details of both datasets were described previously . In brief, the grey matter from the dorsolateral prefrontal cortex (DLPFC) was dissected while still frozen. RNA was extracted for transcriptome library construction following the dUTP protocol and Illumina sequencing. The extracted DNA was processed on the Illumina Infinium HumanMethylation450 BeadChip. An informed consent was signed by the participant and/or legal guardian of the individuals included in this study. IRB approval was approved by each institution. Genotype data The genotyping in CH was conducted on the Illumina platforms (Illumina @ ). Standard QC metrics were applied using PLINK (v1.9) . Individuals with genotype missingness ≥ 2% were removed and the SNPs were removed if their MAF ≤ 1% or Hardy–Weinberg equilibrium p value < 1 × 10 –6 . The genotyping data of the NHW in ROSMAP were described in detail previously . Briefly, the genotyping was measured on the Affymetrix GeneChip 6.0 platform (Santa Clara, CA, USA) at the Broad Institute’s Center for Genotyping or the Translational Genomics Research Institute, and the Illumina OmniQuad Express platform at Children’s Hospital of Philadelphia. With PLINK, we applied the following QC filters: a genotype call rate > 95%, MAF > 0.01, mishap test < 1 × 10 –9 , and a Hardy–Weinberg p < 0.001. We imputed missing genotypes using the Haplotype Reference Consortium (HRC) reference panel in both CH and NHW. Annotations of CpG-related SNPs (CGS) The CpG-related single nucleotide polymorphisms (CGSes) are defined as SNPs where either the reference or the variant allele can form the CpG dinucleotides with a nearby nucleotide (Supplementary Fig. 1). With the genotype data, we calculated the dosage of CpG dinucleotides created by the multiple CGSes within each 1 Kb window and tested its association with the risk of Alzheimer’s disease (AD). Prior reports have shown that the promoter sequences of approximately 1 Kb autonomously recapitulated correct DNA methylation in pluripotent cells . In order to conduct a thorough investigation across the whole genome, we applied a sliding-window approach by setting the overlap between the two consecutive windows to be 500 bp, covering half of one window. Brain data of DNA methylation and Braak stage The genome-wide DNA methylation profile was measured by the Infinium MethylationEPIC Kit (Illumina). We checked the control probes, sex mismatches, contamination, and genotype outliers to identify and remove samples that failed quality control. We kept CpG sites with detection P value < 0.01 across all the qualified samples and masked sample-specific CpG sites with new detection P > 0.01 . We further removed sites reported to have cross-hybridization problems  and polymorphic CpG sites . We further corrected the dye bias for all the qualified CpG probes. Finally, 179 CH samples with 675,583 autosomal probes passing QC were included in the current study. The measurement of Braak stage is described here . Brain RNA-seq data Total RNA was extracted using Qiagen’s RNeasy Mini Kit and sent to the New York Genome Center for transcriptome library construction. Sequencing was done on a NovaSeq 6000 flow cell using 2 × 100 bp cycles, targeting 60 million reads per sample. All the samples included in the analysis passed QC metrics using FastQC . Gene counts were calculated using the featureCounts ﻿function. We applied ComBat-seq to correct batch effects. As a result, a total of 58,942 unique transcripts, including protein coding genes, pseudogenes, long non-coding and antisense RNA, passed QC metrics and exhibited non-zero expression across all participants. Statistical analysis We scaled the dosage of each window to fit within a value from zero to 2 and tested the association of the scaled dosage with clinical diagnosis of AD using generalized linear mixed models (GLMMs) implemented in GMMAT  with adjustments for age, sex, population substructure, genomic relationship matrix (GRM), and genotyping batches. Genome-wide significance threshold was p < 5.0 × 10 –8 . For the mQTL analysis, brain tissue was available in 112 CH  and 571 NHW participants with both genotype and brain DNA methylation data. We used generalized linear models adjusting for the age at death, sex, and technical covariates of genotyping and methylation batches, and methylation chip and position. We analyzed both the cis- and trans-effect of the DNA methylation on gene expression. For the cis-effect of DNA methylation on gene expression, we conducted a highly adaptive sum of powered score-weighted test (aSPUw) by collapsing all the available CpG sites within 100 Kb distance of the gene (from 50 Kb upstream of the transcription start site and 50 Kb downstream of the end site of the gene according to GENCODE v44 (GRCh37) annotation) with the adjustments for age, sex, and technical covariates of methylation chip ID and chip position. For the trans-effect of DNA methylation on gene expression, we used the linear mixed model to control for the random effect of methylation array, the fixed covariates of chip position on the methylation array, the batch effects, age at death, and sex. To apply a similar regression model as the clinical diagnosis of AD, we dichotomized the Braak stage variableby coding stages 5 and 6 as 1 and stages from 1 to 4 as 0. To test the effect of DNA methylation on Braak stage, we conducted the aSUPw test bycollapsing CpG sites within 100 Kb distance of the gene. To test the effect of mRNA expression on Braak stage, used a logistic regression model with the binary Braak stage as the outcome and the mRNA expression level of each gene as the independent variable adjusting for age, sex, and RIN score representing the RNA integrity. Protein–protein interactive network and pathway analysis There were 69 CpG sites annotated to 65 genes associated with the mRNA expression level in human brains. We investigated their network enrichment and pathway analysis using STRING ( https://string-db.org ). Summary statistics of African Americans In order to replicate the results, we downloaded the summary statistics from the most recent published GWAS of AD in African Americans . We extracted the CGS for the top windows identified in the CH, and tested the optimized sequence kernel association tests (SKATO) using the R ‘sumFREGAT’ package ( https://cran.r-project.org/web/packages/sumFREGAT/index.html ).   Cohorts included for genetic studies We included 7,155 CH from the Washington Heights-Inwood Columbia Aging Project (WHICAP)  and the Estudio Familiar de Influencia Genética en Alzheimer (EFIGA) . The WHICAP study is an ongoing prospective, community-based, multiethnic longitudinal study of Medicare beneficiaries 65 years and older residing in northern Manhattan (Washington Heights, Hamilton Heights, and Inwood). All the participants underwent a comprehensive examination including the assessment of general health and function, standardized physical and neurological examination, and a neuropsychological battery of tests. Follow-up visits were performed every 1.5–2 years, repeating similar examinations. Initiated in 1998, EFIGA recruited individuals of CH ancestry including familial and sporadic AD. The individuals were recruited in New York City using local newspapers, the local CH radio station, and postings throughout the Washington Heights-Inwood neighborhood. AD was defined as any individual meeting NINCDS-ADRDA criteria for probable or possible AD . The severity of dementia was rated according to the Clinical Dementia Rating . We also analyzed 1,283 NHW from the Religious Order Study and the Memory & Aging Project (ROSMAP) study to investigate whether the top loci identified in the CH can be generalized to NHW. ROSMAP recruits older individuals without known dementia and their detailed information of both ante-mortem and postmortem phenotyping were collected . For this study, we have included in total 1,283 NHW with whole-genome sequencing data and clinical diagnosis of AD. Cohorts with brain DNA methylation and RNA sequencing (RNA-seq) New York Brain Bank (NYBB): Tissue from the prefrontal cortex came from The NIA Alzheimer’s disease family-based study (NIA-AD FBS), WHICAP, EFIGA, and NCRAD. The NIA-AD FBS included 9,682 family members, and 1,096 unrelated, nondemented elderly from different race/ethnicity groups from 1,756 families with suspected AD. NCRAD included unaffected individuals from families with a history of AD. A description of the families has been previously detailed in a report . University of California, Davis Alzheimer’s Disease Center (UCD ADC): With the goal to conduct research on diversity and risk of AD dementia, UCD applied an active community outreach approach to recruit the individuals from the communities of Alameda, Contra Costa, Sacramento, San Joaquin, Solano, and Yolo County. The overall percentage of CH individuals 60 years of age and older residing in these counties ranged from 7.1 to 14.3% . Brain frontal cortex was dissected to measure DNA methylation and RNA sequencing. Florida Autopsied Multi-Ethnic (FLAME) cohort: The FLAME cohort is derived from the State of Florida brain bank housed at the Mayo Clinic Florida . The FLAME cohort consists of a total of 2,809 autopsied individuals with a wide range of neurodegenerative diseases, who were self-identified as Hispanic/Latino, black/African, and non-Hispanic white/European. The fixed hemi-brain (typically left hemisphere) was weighed, and the frontal cortex was cut and then placed in 10% formalin solution. The University of Pennsylvania Integrated Neurodegenerative Disease Biobank: Patients with neurodegenerative disease are recruited into the autopsy program by the different clinical cores. The subjects selected for the autopsy were followed in the clinical centers with detailed clinical information and most of them were also collected with biofluid, neuroimaging, and genetic data/samples. The left hemisphere and brain stem were immersed in 10% neutral buffered formalin for 2 weeks, whereas the right hemisphere was sliced coronally and frozen. Brain frontal cortex was dissected to measure DNA methylation and RNA sequencing. University of California, San Diego Alzheimer’s Disease Research Center (UCSD ADC): Postmortem frontal cortex tissue from the center’s longitudinally followed cohort was used for this study. Blocks of tissue were provided from autopsy-verified cases after fixation in 10% formalin for 4 weeks. Cases were selected using detailed clinical, biomarker and demographics information collected at visits. The Religious Order Study and the Memory & Aging Project (ROSMAP): We included 516 NHW who have measurements of both postmortem brain DNA methylation and RNA sequencing (RNA-seq) from postmortem brain tissues from the dorsolateral prefrontal cortex. The details of both datasets were described previously . In brief, the grey matter from the dorsolateral prefrontal cortex (DLPFC) was dissected while still frozen. RNA was extracted for transcriptome library construction following the dUTP protocol and Illumina sequencing. The extracted DNA was processed on the Illumina Infinium HumanMethylation450 BeadChip. An informed consent was signed by the participant and/or legal guardian of the individuals included in this study. IRB approval was approved by each institution.   We included 7,155 CH from the Washington Heights-Inwood Columbia Aging Project (WHICAP)  and the Estudio Familiar de Influencia Genética en Alzheimer (EFIGA) . The WHICAP study is an ongoing prospective, community-based, multiethnic longitudinal study of Medicare beneficiaries 65 years and older residing in northern Manhattan (Washington Heights, Hamilton Heights, and Inwood). All the participants underwent a comprehensive examination including the assessment of general health and function, standardized physical and neurological examination, and a neuropsychological battery of tests. Follow-up visits were performed every 1.5–2 years, repeating similar examinations. Initiated in 1998, EFIGA recruited individuals of CH ancestry including familial and sporadic AD. The individuals were recruited in New York City using local newspapers, the local CH radio station, and postings throughout the Washington Heights-Inwood neighborhood. AD was defined as any individual meeting NINCDS-ADRDA criteria for probable or possible AD . The severity of dementia was rated according to the Clinical Dementia Rating . We also analyzed 1,283 NHW from the Religious Order Study and the Memory & Aging Project (ROSMAP) study to investigate whether the top loci identified in the CH can be generalized to NHW. ROSMAP recruits older individuals without known dementia and their detailed information of both ante-mortem and postmortem phenotyping were collected . For this study, we have included in total 1,283 NHW with whole-genome sequencing data and clinical diagnosis of AD.   New York Brain Bank (NYBB): Tissue from the prefrontal cortex came from The NIA Alzheimer’s disease family-based study (NIA-AD FBS), WHICAP, EFIGA, and NCRAD. The NIA-AD FBS included 9,682 family members, and 1,096 unrelated, nondemented elderly from different race/ethnicity groups from 1,756 families with suspected AD. NCRAD included unaffected individuals from families with a history of AD. A description of the families has been previously detailed in a report . University of California, Davis Alzheimer’s Disease Center (UCD ADC): With the goal to conduct research on diversity and risk of AD dementia, UCD applied an active community outreach approach to recruit the individuals from the communities of Alameda, Contra Costa, Sacramento, San Joaquin, Solano, and Yolo County. The overall percentage of CH individuals 60 years of age and older residing in these counties ranged from 7.1 to 14.3% . Brain frontal cortex was dissected to measure DNA methylation and RNA sequencing. Florida Autopsied Multi-Ethnic (FLAME) cohort: The FLAME cohort is derived from the State of Florida brain bank housed at the Mayo Clinic Florida . The FLAME cohort consists of a total of 2,809 autopsied individuals with a wide range of neurodegenerative diseases, who were self-identified as Hispanic/Latino, black/African, and non-Hispanic white/European. The fixed hemi-brain (typically left hemisphere) was weighed, and the frontal cortex was cut and then placed in 10% formalin solution. The University of Pennsylvania Integrated Neurodegenerative Disease Biobank: Patients with neurodegenerative disease are recruited into the autopsy program by the different clinical cores. The subjects selected for the autopsy were followed in the clinical centers with detailed clinical information and most of them were also collected with biofluid, neuroimaging, and genetic data/samples. The left hemisphere and brain stem were immersed in 10% neutral buffered formalin for 2 weeks, whereas the right hemisphere was sliced coronally and frozen. Brain frontal cortex was dissected to measure DNA methylation and RNA sequencing. University of California, San Diego Alzheimer’s Disease Research Center (UCSD ADC): Postmortem frontal cortex tissue from the center’s longitudinally followed cohort was used for this study. Blocks of tissue were provided from autopsy-verified cases after fixation in 10% formalin for 4 weeks. Cases were selected using detailed clinical, biomarker and demographics information collected at visits. The Religious Order Study and the Memory & Aging Project (ROSMAP): We included 516 NHW who have measurements of both postmortem brain DNA methylation and RNA sequencing (RNA-seq) from postmortem brain tissues from the dorsolateral prefrontal cortex. The details of both datasets were described previously . In brief, the grey matter from the dorsolateral prefrontal cortex (DLPFC) was dissected while still frozen. RNA was extracted for transcriptome library construction following the dUTP protocol and Illumina sequencing. The extracted DNA was processed on the Illumina Infinium HumanMethylation450 BeadChip. An informed consent was signed by the participant and/or legal guardian of the individuals included in this study. IRB approval was approved by each institution.   The genotyping in CH was conducted on the Illumina platforms (Illumina @ ). Standard QC metrics were applied using PLINK (v1.9) . Individuals with genotype missingness ≥ 2% were removed and the SNPs were removed if their MAF ≤ 1% or Hardy–Weinberg equilibrium p value < 1 × 10 –6 . The genotyping data of the NHW in ROSMAP were described in detail previously . Briefly, the genotyping was measured on the Affymetrix GeneChip 6.0 platform (Santa Clara, CA, USA) at the Broad Institute’s Center for Genotyping or the Translational Genomics Research Institute, and the Illumina OmniQuad Express platform at Children’s Hospital of Philadelphia. With PLINK, we applied the following QC filters: a genotype call rate > 95%, MAF > 0.01, mishap test < 1 × 10 –9 , and a Hardy–Weinberg p < 0.001. We imputed missing genotypes using the Haplotype Reference Consortium (HRC) reference panel in both CH and NHW.   The CpG-related single nucleotide polymorphisms (CGSes) are defined as SNPs where either the reference or the variant allele can form the CpG dinucleotides with a nearby nucleotide (Supplementary Fig. 1). With the genotype data, we calculated the dosage of CpG dinucleotides created by the multiple CGSes within each 1 Kb window and tested its association with the risk of Alzheimer’s disease (AD). Prior reports have shown that the promoter sequences of approximately 1 Kb autonomously recapitulated correct DNA methylation in pluripotent cells . In order to conduct a thorough investigation across the whole genome, we applied a sliding-window approach by setting the overlap between the two consecutive windows to be 500 bp, covering half of one window.   The genome-wide DNA methylation profile was measured by the Infinium MethylationEPIC Kit (Illumina). We checked the control probes, sex mismatches, contamination, and genotype outliers to identify and remove samples that failed quality control. We kept CpG sites with detection P value < 0.01 across all the qualified samples and masked sample-specific CpG sites with new detection P > 0.01 . We further removed sites reported to have cross-hybridization problems  and polymorphic CpG sites . We further corrected the dye bias for all the qualified CpG probes. Finally, 179 CH samples with 675,583 autosomal probes passing QC were included in the current study. The measurement of Braak stage is described here .   Total RNA was extracted using Qiagen’s RNeasy Mini Kit and sent to the New York Genome Center for transcriptome library construction. Sequencing was done on a NovaSeq 6000 flow cell using 2 × 100 bp cycles, targeting 60 million reads per sample. All the samples included in the analysis passed QC metrics using FastQC . Gene counts were calculated using the featureCounts ﻿function. We applied ComBat-seq to correct batch effects. As a result, a total of 58,942 unique transcripts, including protein coding genes, pseudogenes, long non-coding and antisense RNA, passed QC metrics and exhibited non-zero expression across all participants.   We scaled the dosage of each window to fit within a value from zero to 2 and tested the association of the scaled dosage with clinical diagnosis of AD using generalized linear mixed models (GLMMs) implemented in GMMAT  with adjustments for age, sex, population substructure, genomic relationship matrix (GRM), and genotyping batches. Genome-wide significance threshold was p < 5.0 × 10 –8 . For the mQTL analysis, brain tissue was available in 112 CH  and 571 NHW participants with both genotype and brain DNA methylation data. We used generalized linear models adjusting for the age at death, sex, and technical covariates of genotyping and methylation batches, and methylation chip and position. We analyzed both the cis- and trans-effect of the DNA methylation on gene expression. For the cis-effect of DNA methylation on gene expression, we conducted a highly adaptive sum of powered score-weighted test (aSPUw) by collapsing all the available CpG sites within 100 Kb distance of the gene (from 50 Kb upstream of the transcription start site and 50 Kb downstream of the end site of the gene according to GENCODE v44 (GRCh37) annotation) with the adjustments for age, sex, and technical covariates of methylation chip ID and chip position. For the trans-effect of DNA methylation on gene expression, we used the linear mixed model to control for the random effect of methylation array, the fixed covariates of chip position on the methylation array, the batch effects, age at death, and sex. To apply a similar regression model as the clinical diagnosis of AD, we dichotomized the Braak stage variableby coding stages 5 and 6 as 1 and stages from 1 to 4 as 0. To test the effect of DNA methylation on Braak stage, we conducted the aSUPw test bycollapsing CpG sites within 100 Kb distance of the gene. To test the effect of mRNA expression on Braak stage, used a logistic regression model with the binary Braak stage as the outcome and the mRNA expression level of each gene as the independent variable adjusting for age, sex, and RIN score representing the RNA integrity.   There were 69 CpG sites annotated to 65 genes associated with the mRNA expression level in human brains. We investigated their network enrichment and pathway analysis using STRING ( https://string-db.org ).   In order to replicate the results, we downloaded the summary statistics from the most recent published GWAS of AD in African Americans . We extracted the CGS for the top windows identified in the CH, and tested the optimized sequence kernel association tests (SKATO) using the R ‘sumFREGAT’ package ( https://cran.r-project.org/web/packages/sumFREGAT/index.html ).   Characteristics of the individuals providing blood and brain samples For the analysis of clinical AD diagnosis, we included blood samples from 7,155 CH and 1,238 NHW individuals (Table ). The population stratification of CH against the reference 1000 Genome Project is presented in Supplementary Fig. 2. The mean age of CH is 75 years, while it is 89 years for NHW individuals. 66% of both CH and NHW were women. 37% of CH and 15% NHW carried APOE ε4 allele. There were brain samples available from 179 CH and 571 NHW individuals (Table ). The mean age at death for CH is 80 years, while it is 88 years for NHW individuals. 57.54% of autopsied CH and 62.9% of NHW were women. Their detailed characteristics by different study site were presented in the Supplementary Table 1. CpG identification Within the 7,155 CH participants, 1,857,611 1Kb windows genome-wide, with at least two CpG sites, were tested for association with the clinical diagnosis of AD. Using the Bonferroni-corrected genome-wide significance p value of < 5.0 × 10 –8 , we identified six genome-wide significant regions: ADAM20 (Score = 55.19, P = 4.06 × 10 –8 ), the intergenic region between VRTN and SYNDIG1L (Score = − 37.67, P = 2.25 × 10 –9 ), SPG7 (16q24.3) (Score = 40.51, P = 2.23 × 10 –8 ), PVRL2 (Score = 125.86, P = 1.64 × 10 –9 ), TOMM40 (Score = − 18.58, P = 4.61 × 10 –8 ), and APOE (Score = 75.12, P = 7.26 × 10 –26 ). (Fig. & Table ). The CGS windows in PVRL2 and APOE were also significant in the 1,283 NHW participants from ROSMAP and 9,168 African Americans (Supplementary Table 2). However, the top CGS windows in the NHW were located in a highly linked genetic region covering TOMM40 , APOE , APOC1 , and APOC1P1 (Fig. and Supplementary Table 3). In addition, there were no sex-specific differences for the top six loci identified in the CH (Supplementary Table 4). Cis-effects of CGS on DNA methylation We tested the cis-effects of CGS on molecular phenotypes within 100 Kb flanking the gene. The cis-effects on DNA methylation of the CpG dosage in the windows of AD are presented in Table and Supplementary Fig. 3. Except for ADAM20 , all the other five loci have significant associations between the CGSes dosage and the DNA methylation level of the CpG sites within the cis-regions: the intergenic region between VRTN and SYNDIG1L (cg16837088, b = − 0.04, P = 2.94 × 10 –3 ), SPG7 (cg26536240, b = 0.02, P = 5.78 × 10 –7 ), PVRL2 (cg04406254, b = 0.02, P = 2.49 × 10 –3 ), TOMM40 (cg20051876, b = − 0.04, P = 0.02), and APOE (cg20090143, b = − 0.01, P = 0.02). In NHW, although the same CpG sites at SPG7 ( b = 1.75 × 10 –2 , P = 6.37 × 10 –56 ) and PVRL2 ( b = 8.88 × 10 –3 , P = 1.68 × 10 –4 ) showed statistical significance, the top significant CpG sites are different: SPG7 (cg02244288, b = − 0.01, P = 2.76 × 10 –63 ) and PVRL2 (cg02613937, b = − 0.01, P = 2.27 × 10 –6 ). Different CpG sites in APOE (cg02613937, b = − 0.01, P = 2.36 × 10 –6 ) showed significance in NHW. The cis-mQTLs at ADAM20 (cg04910453, b = − 0.02, P = 0.05) reached nominal significance ( P ≤ 0.05) in NHW but not in CH. DNA methylation levels altering downstream cis-mRNA expression Next, we tested the methylation sites cis-regulated by AD-associated CGSes (identified above), to determine whether these sites altered downstream mRNA expression in the brain. Since our findings revealed different methylation sites for the same gene in CH and NHW for several AD-associated loci, we conducted an aggregate analysis by collapsing all the CpG sites within the cis region of the targeted gene (Table ). We found that except for SYNDIG1L , methylation levels in all the other genes significantly altered the brain RNA expression in CH ( P ≤ 0.05). The significance was replicated for VRTN and TOMM40 in NHW ( P ≤ 0.05). Trans-effects of DNA methylation levels on gene expression We tested whether the expression of the genes that harbor AD-associated CGS were influenced by genome-wide CpG sites in trans. We identified 69 CpG sites across the genome that regulated gene expression of ADAM20 , SYNDIG1L , SPG7 , PVRL2 , TOMM40 , and APOE in CH at genome-wide significant levels after Bonferroni correction of the number of CpG sites included into the analysis (Supplementary Table 5). At PVRL2 and TOMM40 , the same CpG sites regulating the gene expression in CH also regulated the gene expression in NHW ( P < 0.05). These 69 CpG sites that had trans-effects on the gene expressions were annotated to 65 genes. We combined these 65 genes with the target genes of ADAM20 , SYNDIG1L , SPG7 , PVRL2 , TOMM40 , and APOE , and uploaded to STRINGdb to query the significant biological pathways. The significant pathways (FDR < 0.05) are presented in Table , which involved neuron projection and glutamatergic synapse (FDR = 0.0189). Effect of brain DNA methylation and mRNA expression on postmortem Braak stage We collapsed all the CpG sites within the cis region of the targeted gene and all six genes have significant effects on Braak stage (Table ). The downstream mRNA expression of ADAM20 , SYNDIG1L , and TOMM40 also have significant effects on Braak stage.   For the analysis of clinical AD diagnosis, we included blood samples from 7,155 CH and 1,238 NHW individuals (Table ). The population stratification of CH against the reference 1000 Genome Project is presented in Supplementary Fig. 2. The mean age of CH is 75 years, while it is 89 years for NHW individuals. 66% of both CH and NHW were women. 37% of CH and 15% NHW carried APOE ε4 allele. There were brain samples available from 179 CH and 571 NHW individuals (Table ). The mean age at death for CH is 80 years, while it is 88 years for NHW individuals. 57.54% of autopsied CH and 62.9% of NHW were women. Their detailed characteristics by different study site were presented in the Supplementary Table 1.   Within the 7,155 CH participants, 1,857,611 1Kb windows genome-wide, with at least two CpG sites, were tested for association with the clinical diagnosis of AD. Using the Bonferroni-corrected genome-wide significance p value of < 5.0 × 10 –8 , we identified six genome-wide significant regions: ADAM20 (Score = 55.19, P = 4.06 × 10 –8 ), the intergenic region between VRTN and SYNDIG1L (Score = − 37.67, P = 2.25 × 10 –9 ), SPG7 (16q24.3) (Score = 40.51, P = 2.23 × 10 –8 ), PVRL2 (Score = 125.86, P = 1.64 × 10 –9 ), TOMM40 (Score = − 18.58, P = 4.61 × 10 –8 ), and APOE (Score = 75.12, P = 7.26 × 10 –26 ). (Fig. & Table ). The CGS windows in PVRL2 and APOE were also significant in the 1,283 NHW participants from ROSMAP and 9,168 African Americans (Supplementary Table 2). However, the top CGS windows in the NHW were located in a highly linked genetic region covering TOMM40 , APOE , APOC1 , and APOC1P1 (Fig. and Supplementary Table 3). In addition, there were no sex-specific differences for the top six loci identified in the CH (Supplementary Table 4).   We tested the cis-effects of CGS on molecular phenotypes within 100 Kb flanking the gene. The cis-effects on DNA methylation of the CpG dosage in the windows of AD are presented in Table and Supplementary Fig. 3. Except for ADAM20 , all the other five loci have significant associations between the CGSes dosage and the DNA methylation level of the CpG sites within the cis-regions: the intergenic region between VRTN and SYNDIG1L (cg16837088, b = − 0.04, P = 2.94 × 10 –3 ), SPG7 (cg26536240, b = 0.02, P = 5.78 × 10 –7 ), PVRL2 (cg04406254, b = 0.02, P = 2.49 × 10 –3 ), TOMM40 (cg20051876, b = − 0.04, P = 0.02), and APOE (cg20090143, b = − 0.01, P = 0.02). In NHW, although the same CpG sites at SPG7 ( b = 1.75 × 10 –2 , P = 6.37 × 10 –56 ) and PVRL2 ( b = 8.88 × 10 –3 , P = 1.68 × 10 –4 ) showed statistical significance, the top significant CpG sites are different: SPG7 (cg02244288, b = − 0.01, P = 2.76 × 10 –63 ) and PVRL2 (cg02613937, b = − 0.01, P = 2.27 × 10 –6 ). Different CpG sites in APOE (cg02613937, b = − 0.01, P = 2.36 × 10 –6 ) showed significance in NHW. The cis-mQTLs at ADAM20 (cg04910453, b = − 0.02, P = 0.05) reached nominal significance ( P ≤ 0.05) in NHW but not in CH.   Next, we tested the methylation sites cis-regulated by AD-associated CGSes (identified above), to determine whether these sites altered downstream mRNA expression in the brain. Since our findings revealed different methylation sites for the same gene in CH and NHW for several AD-associated loci, we conducted an aggregate analysis by collapsing all the CpG sites within the cis region of the targeted gene (Table ). We found that except for SYNDIG1L , methylation levels in all the other genes significantly altered the brain RNA expression in CH ( P ≤ 0.05). The significance was replicated for VRTN and TOMM40 in NHW ( P ≤ 0.05).   We tested whether the expression of the genes that harbor AD-associated CGS were influenced by genome-wide CpG sites in trans. We identified 69 CpG sites across the genome that regulated gene expression of ADAM20 , SYNDIG1L , SPG7 , PVRL2 , TOMM40 , and APOE in CH at genome-wide significant levels after Bonferroni correction of the number of CpG sites included into the analysis (Supplementary Table 5). At PVRL2 and TOMM40 , the same CpG sites regulating the gene expression in CH also regulated the gene expression in NHW ( P < 0.05). These 69 CpG sites that had trans-effects on the gene expressions were annotated to 65 genes. We combined these 65 genes with the target genes of ADAM20 , SYNDIG1L , SPG7 , PVRL2 , TOMM40 , and APOE , and uploaded to STRINGdb to query the significant biological pathways. The significant pathways (FDR < 0.05) are presented in Table , which involved neuron projection and glutamatergic synapse (FDR = 0.0189).   We collapsed all the CpG sites within the cis region of the targeted gene and all six genes have significant effects on Braak stage (Table ). The downstream mRNA expression of ADAM20 , SYNDIG1L , and TOMM40 also have significant effects on Braak stage.   We have conducted the first multi-omics investigation of CpG-related SNPs (CGS) in brain tissue from a group of individuals of CH ancestry, which confer both genetic and epigenetic effects among individuals. Our study is one of the largest genome-wide association studies with the focus on CGS in this ethnic group. We then assessed the effect cascade from the AD-associated CGSes to brain methylation levels to brain mRNA expression levels. This study was unique in terms of its use of human brain tissues for AD in CH. In addition, the current study provided robust results which survived the most stringent Bonferroni correction for multiple testing. Results from this study emphasize the importance of studying minority groups. Many of the top CGS windows found in NHW were also significant in CH; however, many of the top CGS windows identified in CH were not replicated in NHW. We identified six genome-wide significant windows in or near ADAM20 , VRTN , SYNDIG1L , SPG7 , PVRL2 , TOMM40 , and APOE , where the dosage of the CpG dinucleotides (created by the including CGSes) were associated with the risk of clinical diagnosis of AD. In SPG7, the AD-associated CGS window is associated with increased cis-DNA methylation levels in the frontal cortex, which in turn reduced downstream mRNA expression. We validated the SPG7 genetic and epigenetic alterations in NHW, but did not find an effect on mRNA expression. Similarly, for PVRL2 and APOE, we identified AD-associated CGSes which in turn regulated methylation levels in both CH and NHW brains. However, the epigenetic modifications had muted effect on downstream gene expression. At PVRL2 , both the cis-effects and trans-effects were statistically significant. SPG7 gene encodes paraplegin, a component of the m-AAA protease, an ATP-dependent proteolytic complex of the mitochondrial inner membrane that degrades misfolded proteins and regulates ribosome assembly. Our finding of its significant effects of its association with AD was consistent with the previous report that the DNA methylation level at SPG7 was associated with Braak neurofibrillary stages . PVRL2 (a.k.a. NECTIN2 ) encodes a gene within the nectin subfamily of immunoglobulin-like adhesion molecules that participate in Ca 2+ -independent cell–cell adhesion. It is upstream of TOMM40 and APOE and is located within the highly linked genetic cluster of TOMM40 - APOE - APOC2 . PVRL2 had both cis- and trans-effects between DNA methylation and mRNA gene expression. The CpG island within APOE was reported to have lower DNA methylation levels in AD patients compared to controls in human postmortem brains , which is more profound in glial cells . Lee et al  reported a negative correlation between APOE total RNA and DNA methylation levels at the CpG island within APOE in human postmortem frontal lobes, and this negative correlation is stronger in controls compared to AD patients. SYNDIG1L (also known as TMEM90A or CAPUCIN ) encodes synapse differentiation-induced gene 1 like. In rodents, memory and motor deficits caused by 1,2-Diacetylbenzene via alteration of the mRNA expression of Syndig1l  can be improved by prolactin. Although this investigation is currently one of the the largest with CH brain DNA methylation data, it does have limitations of potential bias by grey vs. white matter composition driven by different protocols used by different brain banks. In addition, the fact that multiple sites contribute to the brain samples may also bring variations into the findings. Since the brain samples from different sites were measured in different methylation batches, we included batch (but not the contributing site) as a covariate in the regression model to remove the colinear bias. In addition, we only investigated DNA methylation patterns in the human postmortem brain. The brain is the most relevant tissue to study AD, and DNA methylation is tissue specific which presents a challenge to generalize the findings from human brains to peripheral blood. In addition, our cross-sectional study design does not account for change in DNA methylation due to normal aging, although we adjusted for age in the regression model. Generally, the higher dosage of CGS in a window should lead to higher methylation levels in that window, the effect direction of the CGS dosage on a single CpG site that is not included within the window are unknown. In such cases, it is reasonable to have the negative association between the CGS dosage of the window and methylation level of CpG site within the 100 Kb distance to the annotated gene, such as VRTN and SYNDIG1L , TOMM40 , and APOE . We report six statistically robust genetic loci covering seven genes that act as a hub for both the genetic and epigenetic effects on clinical diagnosis of AD in CH: ADAM20 , the intergenic region between VRTN and SYNDIG1L , SPG7 , PVRL2 , TOMM40 , and APOE . PVRL2 and APOE were also genetically significant in NHW. Except ADAM20 , all the other loci have significant mQTL effects in CH, and SPG7 , PVRL2 , APOE also have significant mQTL in NHW. The DNA methylation levels of all seven genes except for SYNDIG1L have significant associations with its mRNA gene expression levels in CH brains, while only VRTN and TOMM40 also showed significant associations on mRNA expression levels in NHW brains. Except for VRTN , the mRNA gene expression levels of all the other six genes have significant trans-effects from DNA methylation levels of the CpG sites in CH, while only PVRL2 and TOMM40 also showed trans-effects in NHW. PVRL2 had both significant cis- and trans-effects from the genetics to epigenetics and then to the mRNA gene expression. The genes for the trans-effects are enriched in the pathways of neuron projection and glutamatergic synapse. SPG7 and APOE had significant cis-effects, while SYNDIG1L has significant trans-effects. In addition, their downstream effects on mRNA expression maybe ethnic specific and different from NHW. Finally, the findings in the Hispanics cannot be fully generalized to the non-Hispanic Whites, which might be because of the genetic differences between diverse ancestries.   Below is the link to the electronic supplementary material. Supplementary file1 (DOCX 49 kb) Supplementary file2 (TIFF 473 kb) Supplementary file3 (TIFF 507 kb) Supplementary file4 (TIFF 660 kb)   