Quality control and integration of genotypes from two calling pipelines for whole genome sequence data in the Alzheimer's disease sequencing project

Population-scale cross-disorder atlas of the human prefrontal cortex at single-cell resolution

Neurodegenerative diseases and serious mental illnesses often exhibit overlapping characteristics, highlighting the potential for shared underlying mechanisms. To facilitate a deeper understanding of these diseases and pave the way for more effective treatments, we have generated a population-scale multi-omics dataset consisting of genotype and single-nucleus transcriptome data from the prefrontal cortex of frozen human brain specimens. Encompassing over 6.3 million nuclei from 1,494 donors, our dataset represents a diverse range of neurodegenerative and serious mental illnesses, including Alzheimer's and Parkinson's diseases, schizophrenia, bipolar disorder and diffuse Lewy body dementia, as well as neurotypical controls. Our dataset offers a unique opportunity to study disease interactions, as 21% of donors had comorbid diagnoses of two or more major brain disorders. Additionally, it includes detailed phenotypic information on neuropsychiatric symptoms, such as apathy and weight loss, which commonly accompany Alzheimer's disease and related dementias. We have performed stringent preprocessing and quality controls, ensuring the reliability and usability of the data. As a commitment to fostering collaborative research, we provide this valuable resource as an online repository, enabling widespread analyses across the scientific community.

Alzheimer's Disease Sequencing Project release 4 whole genome sequencing dataset

INTRODUCTION

The Alzheimer's Disease Sequencing Project (ADSP) is a national initiative to understand the genetic architecture of Alzheimer's disease and related dementias (ADRD) by integrating whole genome sequencing (WGS) with other genetic, phenotypic, and harmonized datasets from diverse populations.

METHODS

The Genome Center for Alzheimer's Disease (GCAD) uniformly processed WGS from 36,361 ADSP samples, including 35,014 genetically unique participants of which 45% are from non-European ancestry, across 17 cohorts in 14 countries in this fourth release (R4).

RESULTS

This sequencing effort identified 387 million bi-allelic variants, 42 million short insertions/deletions, and 6.8 million structural variants. Annotations and quality control data are available for all variants and samples. Additionally, detailed phenotypes from 15,927 participants across 10 domains are also provided. A linkage disequilibrium panel was created using unrelated AD cases and controls.

DISCUSSION

Researchers can access and analyze the genetic data via the National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) Data Sharing Service, the VariXam, or NIAGADS GenomicsDB.

HIGHLIGHTS

We detailed the genetic architecture and quality of the Alzheimer's Disease Sequencing Project release 4 whole genome sequences. We identified 435 million single nucleotide polymorphisms, insertions and deletions, and structural variants from diverse genomes. We harmonized extensive phenotypes, linkage disequilibrium reference panel on subset of samples. Data is publicly available at NIAGADS Data Storage Site, variants and annotations are browsable on two different websites.

Frequency of variants in Mendelian Alzheimer's disease genes within the Alzheimer's Disease Sequencing Project

BackgroundPrior studies examined variants within presenilin-2 (PSEN2), presenilin-1 (PSEN1), and amyloid precursor protein (APP) genes. However, previously-reported clinically-relevant variants and other predicted damaging missense (DM) variants have not been characterized in a newer release of the Alzheimer's Disease Sequencing Project (ADSP).ObjectiveTo characterize previously-reported clinically-relevant variants and DM variants in PSEN2, PSEN1, APP within the participants from the ADSP.MethodsWe identified rare variants (MAF < 1%) in PSEN2, PSEN1, and APP in 14,641 individuals with whole genome sequencing and 16,849 individuals with whole exome sequencing available (Ntotal = 31,490). We additionally curated variants from ClinVar, OMIM, and Alzforum and report carriers of variants in clinical databases as well as predicted DM variants in these genes.ResultsWe detected 31 previously-reported clinically-relevant variants with alternate alleles observed within the ADSP: 4 variants in PSEN2, 25 in PSEN1, and 2 in APP. The overall variant carrier rate for the 31 clinically-relevant variants in the ADSP was 0.3%. We observed that 79.5% of the variant carriers were cases compared to 3.9% were controls. In those with AD, the mean age of onset of AD among carriers of these clinically-relevant variants was 19.6 ± 1.4 years earlier compared with noncarriers (p = 7.8 × 10-57). Additionally, we identified 197 rare variants (MAF < 1%) within ADSP participants not reported in known clinical databases.ConclusionsA small proportion of individuals in the ADSP are carriers of a previously-reported clinically-relevant variant allele for AD and these participants have significantly earlier age of AD onset compared to noncarriers.

Multi-omics study of sex in greater amberjack (Seriola dumerili): Identifying related genes, analyzing sex-biased expression, and developing sex-specific markers

The greater amberjack (Seriola dumerili) is a valuable marine fish with significant breeding potential, but does not exhibit clear sexual dimorphism in morphology. Sex research and the development of sex identification technology are important for breeding purposes. Through genome-wide association analysis (GWAS), we identified one significant sex-related SNP and 18 candidate sex-related SNPs, then obtained one significant sex-related gene (hsd17β1) and 20 candidate sex-related genes (hmbox1, ahcyl1, pdzd2, etc.). Key sex-biased genes (sox2, dmrt2, hsd17β3, rnf145, foxo3, etc.) were identified in mature gonads by transcriptome analysis. These genes are important in greater amberjack sex determination and gonad development. In addition, we developed classical PCR and kompetitive allele-specific PCR (KASP) primers to identify the sex of greater amberjack, with an accuracy of 94.87 % and 100 %, respectively. The sex-specific markers can effectively determine the gender of greater amberjack and evaluate the sex ratio and reproductive potential of the breeding population.

Alzheimer's Disease Sequencing Project Release 4 Whole Genome Sequencing Dataset

The Alzheimer's Disease Sequencing Project (ADSP) is a national initiative to understand the genetic architecture of Alzheimer's Disease and Related Dementias (AD/ADRD) by sequencing whole genomes of affected participants and age-matched cognitive controls from diverse populations. The Genome Center for Alzheimer's Disease (GCAD) processed whole-genome sequencing data from 36,361 ADSP participants, including 35,014 genetically unique participants of which 45% are from non-European ancestry, across 17 cohorts in 14 countries in this fourth release (R4). This sequencing effort identified 387 million bi-allelic variants, 42 million short insertions/deletions, and 2.2 million structural variants. Annotations and quality control data are available for all variants and samples. Additionally, detailed phenotypes from 15,927 participants across 10 domains are also provided. A linkage disequilibrium panel was created using unrelated AD cases and controls. Researchers can access and analyze the genetic data via NIAGADS Data Sharing Service, the VariXam tool, or NIAGADS GenomicsDB.

Association of common and rare variants with Alzheimer's disease in more than 13,000 diverse individuals with whole-genome sequencing from the Alzheimer's Disease Sequencing Project

INTRODUCTION

Alzheimer's disease (AD) is a common disorder of the elderly that is both highly heritable and genetically heterogeneous.

METHODS

We investigated the association of AD with both common variants and aggregates of rare coding and non-coding variants in 13,371 individuals of diverse ancestry with whole genome sequencing (WGS) data.

RESULTS

Pooled-population analyses of all individuals identified genetic variants at apolipoprotein E (APOE) and BIN1 associated with AD (p < 5 × 10-8). Subgroup-specific analyses identified a haplotype on chromosome 14 including PSEN1 associated with AD in Hispanics, further supported by aggregate testing of rare coding and non-coding variants in the region. Common variants in LINC00320 were observed associated with AD in Black individuals (p = 1.9 × 10-9). Finally, we observed rare non-coding variants in the promoter of TOMM40 distinct of APOE in pooled-population analyses (p = 7.2 × 10-8).

DISCUSSION

We observed that complementary pooled-population and subgroup-specific analyses offered unique insights into the genetic architecture of AD.

HIGHLIGHTS

We determine the association of genetic variants with Alzheimer's disease (AD) using 13,371 individuals of diverse ancestry with whole genome sequencing (WGS) data. We identified genetic variants at apolipoprotein E (APOE), BIN1, PSEN1, and LINC00320 associated with AD. We observed rare non-coding variants in the promoter of TOMM40 distinct of APOE.

A multi-region single nucleus transcriptomic atlas of Parkinson's disease

Parkinson's Disease (PD) is a debilitating neurodegenerative disorder, characterized by motor and cognitive impairments, that affects >1% of the population over the age of 60. The pathogenesis of PD is complex and remains largely unknown. Due to the cellular heterogeneity of the human brain and changes in cell type composition with disease progression, this complexity cannot be fully captured with bulk tissue studies. To address this, we generated single-nucleus RNA sequencing and whole-genome sequencing data from 100 postmortem cases and controls, carefully selected to represent the entire spectrum of PD neuropathological severity and diverse clinical symptoms. The single nucleus data were generated from five brain regions, capturing the subcortical and cortical spread of PD pathology. Rigorous preprocessing and quality control were applied to ensure data reliability. Committed to collaborative research and open science, this dataset is available on the AMP PD Knowledge Platform, offering researchers a valuable tool to explore the molecular bases of PD and accelerate advances in understanding and treating the disease.

Blood-derived mitochondrial DNA copy number is associated with Alzheimer disease, Alzheimer-related biomarkers and serum metabolites

BACKGROUND

Blood-derived mitochondrial DNA copy number (mtDNA-CN) is a proxy measurement of mitochondrial function in the peripheral and central systems. Abnormal mtDNA-CN not only indicates impaired mtDNA replication and transcription machinery but also dysregulated biological processes such as energy and lipid metabolism. However, the relationship between mtDNA-CN and Alzheimer disease (AD) is unclear.

METHODS

We performed two-sample Mendelian randomization (MR) using publicly available summary statistics from GWAS for mtDNA-CN and AD to investigate the causal relationship between mtDNA-CN and AD. We estimated mtDNA-CN using whole-genome sequence data from blood and brain samples of 13,799 individuals from the Alzheimer's Disease Sequencing Project. Linear and Cox proportional hazards models adjusting for age, sex, and study phase were used to assess the association of mtDNA-CN with AD. The association of AD biomarkers and serum metabolites with mtDNA-CN in blood was evaluated in Alzheimer's Disease Neuroimaging Initiative using linear regression. We conducted a causal mediation analysis to test the natural indirect effects of mtDNA-CN change on AD risk through the significantly associated biomarkers and metabolites.

RESULTS

MR analysis suggested a causal relationship between decreased blood-derived mtDNA-CN and increased risk of AD (OR = 0.68; P = 0.013). Survival analysis showed that decreased mtDNA-CN was significantly associated with higher risk of conversion from mild cognitive impairment to AD (HR = 0.80; P = 0.002). We also identified significant associations of mtDNA-CN with brain FDG-PET (β = 0.103; P = 0.022), amyloid-PET (β = 0.117; P = 0.034), CSF amyloid-β (Aβ) 42/40 (β=-0.124; P = 0.017), CSF t-Tau (β = 0.128; P = 0.015), p-Tau (β = 0.140; P = 0.008), and plasma NFL (β=-0.124; P = 0.004) in females. Several lipid species, amino acids, biogenic amines in serum were also significantly associated with mtDNA-CN. Causal mediation analyses showed that about a third of the effect of mtDNA-CN on AD risk was mediated by plasma NFL (P = 0.009), and this effect was more significant in females (P < 0.005).

CONCLUSIONS

Our study indicates that mtDNA-CN measured in blood is predictive of AD and is associated with AD biomarkers including plasma NFL particularly in females. Further, we illustrate that decreased mtDNA-CN possibly increases AD risk through dysregulation of mitochondrial lipid metabolism and inflammation.

Hypothesis-based investigation of known AD risk variants reveals the genetic underpinnings of neuropathological lesions observed in Alzheimer's-type dementia

Alzheimer's disease (AD) is the leading cause of dementia worldwide. Besides neurofibrillary tangles and amyloid beta (Aβ) plaques, a wide range of co-morbid neuropathological features can be observed in AD brains. Since AD has a very strong genetic background and displays a wide phenotypic heterogeneity, this study aims at investigating the genetic underpinnings of co-morbid and hallmark neuropathological lesions. This was realized by obtaining the genotypes for 75 AD risk variants from low-coverage whole-genome sequencing data for 325 individuals from the Leuven Brain Collection. Association testing with deeply characterized neuropathological lesions revealed a strong and likely direct effect of rs117618017, a SNP in exon 1 of APH1B, with tau-related pathology. Second, a relation between APOE and granulovacuolar degeneration, a proxy for necroptosis, was also discovered in addition to replication of the well-known association of APOE with AD hallmark neuropathological lesions. Additionally, several nominal associations with AD risk genes were detected for pTDP pathology, α-synuclein lesions and pTau-related pathology. These findings were confirmed in a meta-analysis with three independent cohorts. For example, we replicated a prior association between TPCN1 (rs6489896) and LATE-NC risk. Furthermore, we identified new putative LATE-NC-linked SNPs, including rs7068231, located upstream of ANK3. We found association between BIN1 (rs6733839) and α-synuclein pathology, and replicated a prior association between USP6NL (rs7912495) and Lewy body pathology. Additionally, we also found that UMAD1 (rs6943429) was nominally associated with Lewy body pathology. Overall, these results contribute to a broader general understanding of how AD risk variants discovered in large-scale clinical genome-wide association studies are involved in the pathological mechanisms of AD and indicate the importance of downstream elimination of phenotypic heterogeneity introduced in these studies.

Frequency of Variants in Mendelian Alzheimer's Disease Genes within the Alzheimer's Disease Sequencing Project (ADSP)

BACKGROUND

Prior studies using the ADSP data examined variants within presenilin-2 (PSEN2), presenilin-1 (PSEN1), and amyloid precursor protein (APP) genes. However, previously-reported clinically-relevant variants and other predicted damaging missense (DM) variants have not been characterized in a newer release of the Alzheimer's Disease Sequencing Project (ADSP).

OBJECTIVE

To characterize previously-reported clinically-relevant variants and DM variants in PSEN2, PSEN1, APP within the participants from the ADSP.

METHODS

We identified rare variants (MAF <1%) previously-reported in PSEN2, PSEN1, and APP in the available ADSP sample of 14,641 individuals with whole genome sequencing and 16,849 individuals with whole exome sequencing available for research-use (Ntotal = 31,490). We additionally curated variants in these three genes from ClinVar, OMIM, and Alzforum and report carriers of variants in clinical databases as well as predicted DM variants in these genes.

RESULTS

We detected 31 previously-reported clinically-relevant variants with alternate alleles observed within the ADSP: 4 variants in PSEN2, 25 in PSEN1, and 2 in APP. The overall variant carrier rate for the 31 clinically-relevant variants in the ADSP was 0.3%. We observed that 79.5% of the variant carriers were cases compared to 3.9% were controls. In those with AD, the mean age of onset of AD among carriers of these clinically-relevant variants was 19.6 ± 1.4 years earlier compared with noncarriers (p-value=7.8×10-57).

CONCLUSION

A small proportion of individuals in the ADSP are carriers of a previously-reported clinically-relevant variant allele for AD and these participants have significantly earlier age of AD onset compared to noncarriers.

A Specialized Reference Panel with Structural Variants Integration for Improving Genotype Imputation in Alzheimer's Disease and Related Dementias (ADRD)

We developed an imputation panel for Alzheimer's disease (AD) and related dementias (ADRD) using whole-genome sequencing (WGS) data from the Alzheimer's Disease Sequencing Project (ADSP). Recognizing the significant associations between structural variants (SVs) and AD, and their underrepresentation in existing public reference panels, our panel uniquely integrates single nucleotide variants (SNVs), short insertions and deletions (indels), and SVs. This panel enhances the imputation of disease susceptibility, including rare AD-associated SNVs, indels, and SVs, onto genotype array data, offering a cost-effective alternative to whole-genome sequencing while significantly augmenting statistical power. Notably, we discovered 10 rare indels nominal significant related to AD that are absent in the TOPMed-r2 panel and identified three suggestive significant (p-value < 1E-05) AD-associated SVs in the genes EXOC3L2 and DMPK, were identified. These findings provide new insights into AD genetics and underscore the critical role of imputation panels in advancing our understanding of complex diseases like ADRD.

Key variants via the Alzheimer's Disease Sequencing Project whole genome sequence data

INTRODUCTION

Genome-wide association studies (GWAS) have identified loci associated with Alzheimer's disease (AD) but did not identify specific causal genes or variants within those loci. Analysis of whole genome sequence (WGS) data, which interrogates the entire genome and captures rare variations, may identify causal variants within GWAS loci.

METHODS

We performed single common variant association analysis and rare variant aggregate analyses in the pooled population (N cases = 2184, N controls = 2383) and targeted analyses in subpopulations using WGS data from the Alzheimer's Disease Sequencing Project (ADSP). The analyses were restricted to variants within 100 kb of 83 previously identified GWAS lead variants.

RESULTS

Seventeen variants were significantly associated with AD within five genomic regions implicating the genes OARD1/NFYA/TREML1, JAZF1, FERMT2, and SLC24A4. KAT8 was implicated by both single variant and rare variant aggregate analyses.

DISCUSSION

This study demonstrates the utility of leveraging WGS to gain insights into AD loci identified via GWAS.

The Role of Genomic-Informed Risk Assessments in Predicting Dementia Outcomes

Importance

By integrating genetic and clinical risk factors into genomic-informed dementia risk reports, healthcare providers can offer patients detailed risk profiles to facilitate understanding of individual risk and support the implementation of personalized strategies for promoting brain health.

Objective

To develop a genomic-informed risk assessment composed of family history, genetic, and clinical risk factors and, in turn, evaluate how the risk assessment predicted incident dementia.

Design

This longitudinal study included data from two clinical case-control cohorts with an average of 6.6 visits. Secondary analyses were conducted from July 2023 - March 2024.

Setting

Data were previously collected across multiple US locations from 1994 to 2023.

Participants

Older adults aged 55+ with whole-genome sequencing and dementia-free at baseline.

Exposures

An additive score comprising the modified Cardiovascular Risk Factors, Aging, and Incidence of Dementia Risk Score (mCAIDE), family history of dementia, APOE genotype, and an AD polygenic risk score.

Main Outcomes and Measures

The risk of progression to all-cause dementia was evaluated using Cox-proportional hazard models (hazard ratios with 95% confidence intervals [OR 9%CI]).

Results

A total of 3,429 older adults were included (aged 75 ± 7 years; 59% female; 75% non-Latino White, 15% Black, 5.2% Latino, 3.6% other, and 0.4% Asian; 27% MCI), with 751 participants progressing to dementia. The most common high-risk indicator was a family history of dementia (56%), followed by APOE*ε4 genotype (36%), high mCAIDE score (34%), and high AD-PRS (11%). Most participants had at least one high-risk indicator, with 39% having one, 32% two, 9.8% three, and 1% four. The presence of 1, 2, 3, or 4 risk indicators was associated with a doubling (HR = 1.72, CI: 1.34-2.22, p = 2.5e-05), tripling (HR = 3.09, CI: 2.41-3.95, p = 4.4e-19), quadrupling (HR = 4.46, CI: 3.34-5.94, p = 2.2e-24), and a twelvefold increase (HR = 12.15, CI: 7.33-20.14, p = 3.2e-22) in dementia risk.

Conclusion & Relevance

We found that most participants in memory and aging clinics had at least one high-risk indicator for dementia. Furthermore, we observed a dose-response relationship where a greater number of risk indicators was associated with an increased risk of incident dementia.

Genetic associations with dementia-related proteinopathy: Application of item response theory

INTRODUCTION

Although dementia-related proteinopathy has a strong negative impact on public health, and is highly heritable, understanding of the related genetic architecture is incomplete.

METHODS

We applied multidimensional generalized partial credit modeling (GPCM) to test genetic associations with dementia-related proteinopathies. Data were analyzed to identify candidate single nucleotide variants for the following proteinopathies: Aβ, tau, α-synuclein, and TDP-43.

RESULTS

Final included data comprised 966 participants with neuropathologic and WGS data. Three continuous latent outcomes were constructed, corresponding to TDP-43-, Aβ/Tau-, and α-synuclein-related neuropathology endophenotype scores. This approach helped validate known genotype/phenotype associations: for example, TMEM106B and GRN were risk alleles for TDP-43 pathology; and GBA for α-synuclein/Lewy bodies. Novel suggestive proteinopathy-linked alleles were also discovered, including several (SDHAF1, TMEM68, and ARHGEF28) with colocalization analyses and/or high degrees of biologic credibility.

DISCUSSION

A novel methodology using GPCM enabled insights into gene candidates for driving misfolded proteinopathies.

HIGHLIGHTS

Latent factor scores for proteinopathies were estimated using a generalized partial credit model. The three latent continuous scores corresponded well with proteinopathy severity. Novel genes associated with proteinopathies were identified. Several genes had high degrees of biologic credibility for dementia risk factors.

Genome-wide association studies identify novel loci in rapidly progressive Alzheimer's disease

INTRODUCTION

Recent data suggest that distinct prion-like amyloid beta and tau strains are associated with rapidly progressive Alzheimer's disease (rpAD). The role of genetic factors in rpAD is largely unknown.

METHODS

Previously known AD risk loci were examined in rpAD cases. Genome-wide association studies (GWAS) were performed to identify variants that influence rpAD.

RESULTS

We identified 115 pathology-confirmed rpAD cases and 193 clinical rpAD cases, 80% and 69% were of non-Hispanic European ancestry. Compared to the clinical cohort, pathology-confirmed rpAD had higher frequencies of apolipoprotein E (APOE) ε4 and rare missense variants in AD risk genes. A novel genome-wide significant locus (P < 5×10-8 ) was observed for clinical rpAD on chromosome 21 (rs2832546); 102 loci showed suggestive associations with pathology-confirmed rpAD (P < 1×10-5 ). DISCUSSION rpAD constitutes an extreme subtype of AD with distinct features. GWAS found previously known and novel loci associated with rpAD. Highlights Rapidly progressive Alzheimer's disease (rpAD) was defined with different criteria. Whole genome sequencing identified rare missense variants in rpAD. Novel variants were identified for clinical rpAD on chromosome 21.

Human whole-exome genotype data for Alzheimer's disease

The heterogeneity of the whole-exome sequencing (WES) data generation methods present a challenge to a joint analysis. Here we present a bioinformatics strategy for joint-calling 20,504 WES samples collected across nine studies and sequenced using ten capture kits in fourteen sequencing centers in the Alzheimer's Disease Sequencing Project. The joint-genotype called variant-called format (VCF) file contains only positions within the union of capture kits. The VCF was then processed specifically to account for the batch effects arising from the use of different capture kits from different studies. We identified 8.2 million autosomal variants. 96.82% of the variants are high-quality, and are located in 28,579 Ensembl transcripts. 41% of the variants are intronic and 1.8% of the variants are with CADD > 30, indicating they are of high predicted pathogenicity. Here we show our new strategy can generate high-quality data from processing these diversely generated WES samples. The improved ability to combine data sequenced in different batches benefits the whole genomics research community.

DNA from multiple viral species is associated with Alzheimer's disease risk

INTRODUCTION

Multiple infectious agents, including viruses, bacteria, fungi, and protozoa, have been linked to Alzheimer's disease (AD) risk by independent lines of evidence. We explored this association by comparing the frequencies of viral species identified in a large sample of AD cases and controls.

METHODS

DNA sequence reads that did not align to the human genome in sequences were mapped to viral reference sequences, quantified, and then were tested for association with AD in whole exome sequences (WES) and whole genome sequences (WGS) datasets.

RESULTS

Several viruses were significant predictors of AD according to the machine learning classifiers. Subsequent regression analyses showed that herpes simplex type 1 (HSV-1) (odds ratio [OR] = 3.71, p = 8.03 × 10-4) and human papillomavirus 71 (HPV-71; OR = 3.56, p = 0.02), were significantly associated with AD after Bonferroni correction. The phylogenetic-related cluster of Herpesviridae was significantly associated with AD in several strata of the data (p < 0.01).

DISCUSSION

Our results support the hypothesis that viral infection, especially HSV-1, is associated with AD risk.

Association of Common and Rare Variants with Alzheimer's Disease in over 13,000 Diverse Individuals with Whole-Genome Sequencing from the Alzheimer's Disease Sequencing Project

Alzheimer's Disease (AD) is a common disorder of the elderly that is both highly heritable and genetically heterogeneous. Here, we investigated the association between AD and both common variants and aggregates of rare coding and noncoding variants in 13,371 individuals of diverse ancestry with whole genome sequence (WGS) data. Pooled-population analyses identified genetic variants in or near APOE, BIN1, and LINC00320 significantly associated with AD (p < 5×10-8). Population-specific analyses identified a haplotype on chromosome 14 including PSEN1 associated with AD in Hispanics, further supported by aggregate testing of rare coding and noncoding variants in this region. Finally, we observed suggestive associations (p < 5×10-5) of aggregates of rare coding rare variants in ABCA7 among non-Hispanic Whites (p=5.4×10-6), and rare noncoding variants in the promoter of TOMM40 distinct of APOE in pooled-population analyses (p=7.2×10-8). Complementary pooled-population and population-specific analyses offered unique insights into the genetic architecture of AD.

Key variants via Alzheimer's Disease Sequencing Project whole genome sequence data

INTRODUCTION

Genome-wide association studies (GWAS) have identified loci associated with Alzheimer's disease (AD) but did not identify specific causal genes or variants within those loci. Analysis of whole genome sequence (WGS) data, which interrogates the entire genome and captures rare variations, may identify causal variants within GWAS loci.

METHODS

We performed single common variant association analysis and rare variant aggregate analyses in the pooled population (N cases=2,184, N controls=2,383) and targeted analyses in sub-populations using WGS data from the Alzheimer's Disease Sequencing Project (ADSP). The analyses were restricted to variants within 100 kb of 83 previously identified GWAS lead variants.

RESULTS

Seventeen variants were significantly associated with AD within five genomic regions implicating the genes OARD1/NFYA/TREML1, JAZF1, FERMT2, and SLC24A4. KAT8 was implicated by both single variant and rare variant aggregate analyses.

DISCUSSION

This study demonstrates the utility of leveraging WGS to gain insights into AD loci identified via GWAS.

Admixture mapping implicates 13q33.3 as ancestry-of-origin locus for Alzheimer disease in Hispanic and Latino populations

Alzheimer disease (AD) is the most common form of senile dementia, with high incidence late in life in many populations including Caribbean Hispanic (CH) populations. Such admixed populations, descended from more than one ancestral population, can present challenges for genetic studies, including limited sample sizes and unique analytical constraints. Therefore, CH populations and other admixed populations have not been well represented in studies of AD, and much of the genetic variation contributing to AD risk in these populations remains unknown. Here, we conduct genome-wide analysis of AD in multiplex CH families from the Alzheimer Disease Sequencing Project (ADSP). We developed, validated, and applied an implementation of a logistic mixed model for admixture mapping with binary traits that leverages genetic ancestry to identify ancestry-of-origin loci contributing to AD. We identified three loci on chromosome 13q33.3 associated with reduced risk of AD, where associations were driven by Native American (NAM) ancestry. This AD admixture mapping signal spans the FAM155A, ABHD13, TNFSF13B, LIG4, and MYO16 genes and was supported by evidence for association in an independent sample from the Alzheimer's Genetics in Argentina-Alzheimer Argentina consortium (AGA-ALZAR) study with considerable NAM ancestry. We also provide evidence of NAM haplotypes and key variants within 13q33.3 that segregate with AD in the ADSP whole-genome sequencing data. Interestingly, the widely used genome-wide association study approach failed to identify associations in this region. Our findings underscore the potential of leveraging genetic ancestry diversity in recently admixed populations to improve genetic mapping, in this case for AD-relevant loci.

Pharmacogenomic and Statistical Analysis

Genetic variants can alter response to drugs and other therapeutic interventions. The study of this phenomenon, called pharmacogenomics, is similar in many ways to other types of genetic studies but has distinct methodological and statistical considerations. Genetic variants involved in the processing of exogenous compounds exhibit great diversity and complexity, and the phenotypes studied in pharmacogenomics are also more complex than typical genetic studies. In this chapter, we review basic concepts in pharmacogenomic study designs, data generation techniques, statistical analysis approaches, and commonly used methods and briefly discuss the ultimate translation of findings to clinical care.

Identification of risk genes for Alzheimer's disease by gene embedding

Most disease-gene association methods do not account for gene-gene interactions, even though these play a crucial role in complex, polygenic diseases like Alzheimer's disease (AD). To discover new genes whose interactions may contribute to pathology, we introduce GeneEMBED. This approach compares the functional perturbations induced in gene interaction network neighborhoods by coding variants from disease versus healthy subjects. In two independent AD cohorts of 5,169 exomes and 969 genomes, GeneEMBED identified novel candidates. These genes were differentially expressed in post mortem AD brains and modulated neurological phenotypes in mice. Four that were differentially overexpressed and modified neurodegeneration in vivo are PLEC, UTRN, TP53, and POLD1. Notably, TP53 and POLD1 are involved in DNA break repair and inhibited by approved drugs. While these data show proof of concept in AD, GeneEMBED is a general approach that should be broadly applicable to identify genes relevant to risk mechanisms and therapy of other complex diseases.

Association of mitochondrial variants and haplogroups identified by whole exome sequencing with Alzheimer's disease

INTRODUCTION

Findings regarding the association between mitochondrial DNA (mtDNA) variants and Alzheimer's disease (AD) are inconsistent.

METHODS

We developed a pipeline for accurate assembly and variant calling in mitochondrial genomes embedded within whole exome sequences (WES) from 10,831 participants from the Alzheimer's Disease Sequencing Project (ADSP). Association of AD risk was evaluated with each mtDNA variant and variants located in 1158 nuclear genes related to mitochondrial function using the SCORE test. Gene-based tests were performed using SKAT-O.

RESULTS

Analysis of 4220 mtDNA variants revealed study-wide significant association of AD with a rare MT-ND4L variant (rs28709356 C>T; minor allele frequency = 0.002; P = 7.3 × 10-5 ) as well as with MT-ND4L in a gene-based test (P = 6.71 × 10-5 ). Significant association was also observed with a MT-related nuclear gene, TAMM41, in a gene-based test (P = 2.7 × 10-5 ). The expression of TAMM41 was lower in AD cases than controls (P = .00046) or mild cognitive impairment cases (P = .03).

DISCUSSION

Significant findings in MT-ND4L and TAMM41 provide evidence for a role of mitochondria in AD.

APOE Gene Associated with Cholesterol-Related Traits in the Hispanic Population

Genetic variants in the apolipoprotein E (APOE) gene are associated with lipid metabolism and lipid-related traits in the non-Hispanic population. There have been limited studies regarding the association between the APOE gene and hypercholesterolemia in the Hispanic population; therefore, our aim for this study is to examine the APOE gene’s associations with cholesterol level and its related phenotypes. The APOE gene consists of three different alleles, ε2, ε3, and ε4, with ε4 being associated with dementia and cardiovascular diseases. A total of 1,382 subjects were collected from the Texas Alzheimer’s Research and Care Consortium (TARCC, N = 1320) and the Initial Study of Longevity and Dementia from the Rio Grande Valley (ISLD-RGV, N = 62). Questionnaires on demographics, medical history, and blood/saliva samples were collected and APOE genotypes were performed. We observed allele frequencies of the APOE ε3 (96.7%), ε4 (22.6%) and ε2 (6.8%) alleles, respectively. Multivariable logistic regression revealed a significant association between the APOE ε4 allele and hypercholesteremia (p = 1.8 × 10⁻⁴) in our studied Hispanic population. We prove for the first time, that the APOE ε4 allele increases the risk for hypercholesterol in Hispanics. Further research is needed to confirm and supports our current findings.

A Machine Learning Method to Identify Genetic Variants Potentially Associated With Alzheimer's Disease

There is hope that genomic information will assist prediction, treatment, and understanding of Alzheimer's disease (AD). Here, using exome data from ∼10,000 individuals, we explore machine learning neural network (NN) methods to estimate the impact of SNPs (i.e., genetic variants) on AD risk. We develop an NN-based method (netSNP) that identifies hundreds of novel potentially protective or at-risk AD-associated SNPs (along with an effect measure); the majority with frequency under 0.01. For case individuals, the number of "protective" (or "at-risk") netSNP-identified SNPs in their genome correlates positively (or inversely) with their age of AD diagnosis and inversely (or positively) with autopsy neuropathology. The effect measure increases correlations. Simulations suggest our results are not due to genetic linkage, overfitting, or bias introduced by netSNP. These findings suggest that netSNP can identify SNPs associated with AD pathophysiology that may assist with the diagnosis and mechanistic understanding of the disease.

Analysis of whole genome sequenced cases and controls shows that the association of variants in TOMM40, BCAM, NECTIN2 and APOC1 with late onset Alzheimer's disease is driven by linkage disequilibrium with APOE ε2/ε3/ε4 alleles

Variants in APOE are associated with risk of late onset Alzheimer's disease (LOAD) but the magnitude of the effect has been reported to vary across ancestries. Also, other variants in the region have been reported to show association though it has been unclear whether this was secondary to their linkage disequilibrium with the APOE variants rs429358 and rs7412. Previous analyses of exome-sequenced samples have identified other genes in which rare variants impact risk of disease. In this study 2000 whole genome sequenced cases and controls with different ancestries were subjected to gene-based weighted burden analysis to identify risk genes. Additionally, individual variants in the APOE region were tested for association with LOAD. When using the APOE variants as covariates no individual genes showed statistically significant evidence for association after Bonferroni correction for multiple testing, which may well be a consequence of the modest sample size. Likewise, for those variants initially showing evidence of association with LOAD incorporating the APOE variants as covariates dramatically reduced the strength of association. These results demonstrate that the differential association of APOE across ancestries does not appear to be driven by another variant in the region. It seems likely that no other genes in the region have a direct effect on LOAD risk.

Alzheimer Disease Pathology-Associated Polymorphism in a Complex Variable Number of Tandem Repeat Region Within the MUC6 Gene, Near the AP2A2 Gene

We found evidence of late-onset Alzheimer disease (LOAD)-associated genetic polymorphism within an exon of Mucin 6 (MUC6) and immediately downstream from another gene: Adaptor Related Protein Complex 2 Subunit Alpha 2 (AP2A2). PCR analyses on genomic DNA samples confirmed that the size of the MUC6 variable number tandem repeat (VNTR) region was highly polymorphic. In a cohort of autopsied subjects with quantitative digital pathology data (n = 119), the size of the polymorphic region was associated with the severity of pTau pathology in neocortex. In a separate replication cohort of autopsied subjects (n = 173), more pTau pathology was again observed in subjects with longer VNTR regions (p = 0.031). Unlike MUC6, AP2A2 is highly expressed in human brain. AP2A2 expression was lower in a subset analysis of brain samples from persons with longer versus shorter VNTR regions (p = 0.014 normalizing with AP2B1 expression). Double-label immunofluorescence studies showed that AP2A2 protein often colocalized with neurofibrillary tangles in LOAD but was not colocalized with pTau proteinopathy in progressive supranuclear palsy, or with TDP-43 proteinopathy. In summary, polymorphism in a repeat-rich region near AP2A2 was associated with neocortical pTau proteinopathy (because of the unique repeats, prior genome-wide association studies were probably unable to detect this association), and AP2A2 was often colocalized with neurofibrillary tangles in LOAD.

The MUC6/AP2A2 Locus and Its Relevance to Alzheimer's Disease: A Review

We recently reported evidence of Alzheimer's disease (AD)-linked genetic variation within the mucin 6 (MUC6) gene on chromosome 11p, nearby the adaptor-related protein complex 2 subunit alpha 2 (AP2A2) gene. This locus has interesting features related to human genomics and clinical research. MUC6 gene variants have been reported to potentially influence viral-including herpesvirus-immunity and the gut microbiome. Within the MUC6 gene is a unique variable number of tandem repeat (VNTR) region. We discovered an association between MUC6 VNTR repeat expansion and AD pathologic severity, particularly tau proteinopathy. Here, we review the relevant literature. The AD-linked VNTR polymorphism may also influence AP2A2 gene expression. AP2A2 encodes a polypeptide component of the adaptor protein complex, AP-2, which is involved in clathrin-coated vesicle function and was previously implicated in AD pathogenesis. To provide background information, we describe some key knowledge gaps in AD genetics research. The "missing/hidden heritability problem" of AD is highlighted. Extensive portions of the human genome, including the MUC6 VNTR, have not been thoroughly evaluated due to limitations of existing high-throughput sequencing technology. We present and discuss additional data, along with cautionary considerations, relevant to the hypothesis that MUC6 repeat expansion influences AD pathogenesis.

Hadoop and PySpark for reproducibility and scalability of genomic sequencing studies

Modern genomic studies are rapidly growing in scale, and the analytical approaches used to analyze genomic data are increasing in complexity. Genomic data management poses logistic and computational challenges, and analyses are increasingly reliant on genomic annotation resources that create their own data management and versioning issues. As a result, genomic datasets are increasingly handled in ways that limit the rigor and reproducibility of many analyses. In this work, we examine the use of the Spark infrastructure for the management, access, and analysis of genomic data in comparison to traditional genomic workflows on typical cluster environments. We validate the framework by reproducing previously published results from the Alzheimer's Disease Sequencing Project. Using the framework and analyses designed using Jupyter notebooks, Spark provides improved workflows, reduces user-driven data partitioning, and enhances the portability and reproducibility of distributed analyses required for large-scale genomic studies.

Empirical design of a variant quality control pipeline for whole genome sequencing data using replicate discordance

The success of next-generation sequencing depends on the accuracy of variant calls. Few objective protocols exist for QC following variant calling from whole genome sequencing (WGS) data. After applying QC filtering based on Genome Analysis Tool Kit (GATK) best practices, we used genotype discordance of eight samples that were sequenced twice each to evaluate the proportion of potentially inaccurate variant calls. We designed a QC pipeline involving hard filters to improve replicate genotype concordance, which indicates improved accuracy of genotype calls. Our pipeline analyzes the efficacy of each filtering step. We initially applied this strategy to well-characterized variants from the ClinVar database, and subsequently to the full WGS dataset. The genome-wide biallelic pipeline removed 82.11% of discordant and 14.89% of concordant genotypes, and improved the concordance rate from 98.53% to 99.69%. The variant-level read depth filter most improved the genome-wide biallelic concordance rate. We also adapted this pipeline for triallelic sites, given the increasing proportion of multiallelic sites as sample sizes increase. For triallelic sites containing only SNVs, the concordance rate improved from 97.68% to 99.80%. Our QC pipeline removes many potentially false positive calls that pass in GATK, and may inform future WGS studies prior to variant effect analysis.

Systematic analysis of dark and camouflaged genes reveals disease-relevant genes hiding in plain sight

BACKGROUND

The human genome contains "dark" gene regions that cannot be adequately assembled or aligned using standard short-read sequencing technologies, preventing researchers from identifying mutations within these gene regions that may be relevant to human disease. Here, we identify regions with few mappable reads that we call dark by depth, and others that have ambiguous alignment, called camouflaged. We assess how well long-read or linked-read technologies resolve these regions.

RESULTS

Based on standard whole-genome Illumina sequencing data, we identify 36,794 dark regions in 6054 gene bodies from pathways important to human health, development, and reproduction. Of these gene bodies, 8.7% are completely dark and 35.2% are ≥ 5% dark. We identify dark regions that are present in protein-coding exons across 748 genes. Linked-read or long-read sequencing technologies from 10x Genomics, PacBio, and Oxford Nanopore Technologies reduce dark protein-coding regions to approximately 50.5%, 35.6%, and 9.6%, respectively. We present an algorithm to resolve most camouflaged regions and apply it to the Alzheimer's Disease Sequencing Project. We rescue a rare ten-nucleotide frameshift deletion in CR1, a top Alzheimer's disease gene, found in disease cases but not in controls.

CONCLUSIONS

While we could not formally assess the association of the CR1 frameshift mutation with Alzheimer's disease due to insufficient sample-size, we believe it merits investigating in a larger cohort. There remain thousands of potentially important genomic regions overlooked by short-read sequencing that are largely resolved by long-read technologies.

Benefits and Challenges of Rare Genetic Variation in Alzheimer's Disease

Purpose of Review

It is well established that sporadic Alzheimer's disease (AD) is polygenic with common and rare genetic variation alongside environmental factors contributing to disease. Here, we review our current understanding of the genetic architecture of disease, paying specific attention to rare susceptibility variants, and explore some of the limitations in rare variant detection and analysis.

Recent Findings

Rare variation has been shown to robustly associate with disease. These include potentially damaging and loss of function mutations that are easily modelled in silico, in vitro and in vivo, and represent potentially druggable targets. A number of risk genes, including TREM2, SORL1 and ABCA7 show multiple independent associations suggesting that they may influence disease via multiple mechanisms. With transcriptional regulation, inflammatory response and modification of protein production suggested to be of primary importance.

Summary

We are at the beginning of our journey of rare variant detection in AD. Whole exome sequencing has been the predominant technology of choice. While fruitful, this has introduced a number of challenges with regard to data integration. Ultimately the future of disease-associated rare variant identification lies in whole genome sequencing projects that will allow the testing of the full range of genomic variation.

Rare genetic variation implicated in non-Hispanic white families with Alzheimer disease

OBJECTIVE

To identify genetic variation influencing late-onset Alzheimer disease (LOAD), we used a large data set of non-Hispanic white (NHW) extended families multiply-affected by LOAD by performing whole genome sequencing (WGS).

METHODS

As part of the Alzheimer Disease Sequencing Project, WGS data were generated for 197 NHW participants from 42 families (affected individuals and unaffected, elderly relatives). A two-pronged approach was taken. First, variants were prioritized using heterogeneity logarithm of the odds (HLOD) and family-specific LOD scores as well as annotations based on function, frequency, and segregation with disease. Second, known Alzheimer disease (AD) candidate genes were assessed for rare variation using a family-based association test.

RESULTS

We identified 41 rare, predicted-damaging variants that segregated with disease in the families that contributed to the HLOD or family-specific LOD regions. These included a variant in nitric oxide synthase 1 adaptor protein that segregates with disease in a family with 7 individuals with AD, as well as variants in RP11-433J8, ABCA1, and FISP2. Rare-variant association identified 2 LOAD candidate genes associated with disease in these families: FERMT2 (p-values = 0.001) and SLC24A4 (p-value = 0.009). These genes still showed association while controlling for common index variants, indicating the rare-variant signal is distinct from common variation that initially identified the genes as candidates.

CONCLUSIONS

We identified multiple genes with putative damaging rare variants that segregate with disease in multiplex AD families and showed that rare variation may influence AD risk at AD candidate genes. These results identify novel AD candidate genes and show a role for rare variation in LOAD etiology, even at genes previously identified by common variation.