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Vardarajan, B. N.

Publications and source records attributed to Vardarajan, B. N..

At least 19 recordsLinked to original sources

Multi-omics characterization of vascular, neurodegenerative, and mixed neuropathology in the aging human brain

Late-life cognitive impairment most commonly occurs in the setting of mixed neurodegenerative and cerebrovascular pathology, yet the molecular programs distinguishing vascular, neurodegenerative, and mixed pathology in the aging human brain remain incompletely defined. We performed neuropathology-stratified proteomic and transcriptomic profiling of postmortem brain tissue from participants in the Religious Orders Study and Rush Memory and Aging Project. Dorsolateral prefrontal cortex proteomics (n = 733) were analyzed alongside bulk RNA sequencing from dorsolateral prefrontal cortex (n = 938), posterior cingulate cortex (n = 569), and anterior caudate (n = 632). Participants were classified into vascular, neurodegenerative, and mixed pathology groups based on comprehensive autopsy assessment. Neurodegenerative and mixed pathology, relative to vascular pathology, showed coordinated upregulation of immune and inflammatory pathways and downregulation of mitochondrial and oxidative phosphorylation programs across molecular layers. Although few individual proteins differed between mixed and neurodegenerative groups, pathway-level analyses identified additional remodeling programs in mixed pathology, including extracellular matrix organization and vesicle-mediated transport. Proteomic co-expression network analysis identified immune-stress modules associated with amyloid burden, tau pathology, and cognitive decline, whereas a mitochondrial bioenergetic module showed relative preservation in vascular pathology. Cross-omics concordance was robust at the pathway level but limited at the level of individual genes and proteins. These findings define conserved molecular programs distinguishing vascular, neurodegenerative, and mixed pathology and demonstrate that pathway-level organization provides a stable framework for interpreting molecular heterogeneity in late-life dementia.

genomics↗

Isogenic cortical organoids enable precision targeting of APP variant-specific pathways in Alzheimer's disease

Alzheimers disease (AD) lacks disease-modifying therapies, in part due to the limitations of existing disease models, which have struggled to capture the early pathogenic events leading to neuronal degeneration. Unfortunately, recent therapies targeting hallmarks of AD have proven inefficient in humans, and it is thus necessary to identify alternative targets. Here, by generating an isogenic panel of hiPSC-derived cortical organoids carrying familial AD-associated APP variants or the protective A673T variant, we identified distinct, actionable pathogenic pathways specific to each variant. Proteomic analyses revealed variant-specific molecular disruptions: A673V organoids show impairments in proteostasis and cholesterol metabolism, whereas KM670/671NL organoids exhibit mitochondrial bioenergetic defects. These signatures overlapped with dysregulated proteins in post-mortem AD brains, demonstrating the reliability of our in vitro model. Importantly, targeted interventions restored neuronal survival in a variant-specific manner: overexpression of the master regulator of lysosomal biogenesis, TFEB, rescued A673V neurons, while ferroptosis inhibition selectively protected KM670/671NL neurons. Overall, our results indicate that differential treatments can be tailored based on distinct genetic backgrounds, supporting the development of precision medicine approaches in AD.

neuroscience↗

CoxMDS: Multiple Data Splitting for High-dimensional Mediation Analysis with Survival Outcomes in Epigenome-wide Studies

Causal mediation analysis investigates whether the effect of an exposure on an outcome operates through intermediate variables known as mediators. Although progress has been made in high-dimensional mediation analysis, current methods do not reliably control the false discovery rate (FDR) in finite samples, especially when mediators are moderately to highly correlated or follow non-Gaussian distributions. These challenges frequently arise in DNA methylation studies. We introduce CoxMDS, a multiple data splitting method that uses Cox proportional hazards models to identify putative causal mediators for survival outcomes. CoxMDS ensures finite-sample FDR control even in the presence of correlated or non-Gaussian mediators. Through simulations, CoxMDS is shown to maintain FDR control and achieve higher statistical power compared with existing approaches. In applications to DNA methylation data with survival outcomes, CoxMDS identified eight CpG sites in The Cancer Genome Atlas (TCGA) that are consistent with the hypothesis that DNA methylation may mediate the effect of smoking on lung cancer survival, and two CpG sites in the Alzheimers Disease Neuroimaging Initiative (ADNI) that are consistent with the hypothesis that DNA methylation may mediate the effect of smoking on time to Alzheimers disease conversion.

bioinformatics↗

TPClust: Temporal Profile-Guided Subtyping Using High-Dimensional Omics Data

Clustering is widely used to identify subtypes in heterogeneous populations, yet most approaches rarely integrate longitudinal phenotypic trajectories with high-dimensional molecular profiles, limiting their ability to resolve biologically and clinically meaningful heterogeneity in progressive diseases. We developed TPClust, a supervised, semi-parametric clustering method that integrates high-dimensional omics data with longitudinal phenotypes including outcomes and covariates for outcome-guided subtyping. TPClust jointly models latent subtype membership and longitudinal outcome trajectories using multinomial logistic regression informed by molecular features selected via structured regularization, along with spline-based regression to capture subtype-specific, time-varying covariate effects. Simulations demonstrate valid inference for time-varying effects and robust feature selection. Applied to transcriptomic profiles and longitudinal cognitive data from 1,020 older adults in the Religious Orders Study and the Rush Memory and Aging Project, TPClust identified four aging subtypes including intermediate subtypes not captured by unimodal approaches with distinct cognitive trajectories, time-varying risk profiles, clinical and neuropathological features, and multimodal molecular signatures.

bioinformatics↗

CD33-CD45 Interaction Reveals a Mechanistic Link to Alzheimer's Disease Susceptibility

The innate immune gene CD33, encoding a myeloid inhibitory sialic acid-binding receptor, is associated with Alzheimers disease (AD) susceptibility. The AD-associated rs3865444CC risk variant reduces splicing of the sialic acid-binding domain and increases expression of the full-length (sialic acid-binding) CD33 isoform seven-fold compared to the rs3865444AA protective genotype. Here we identify CD45 as an immune cell-specific sialic acid-dependent cis CD33 binding partner, whose phosphatase activity is inhibited by CD33. Overexpression of CD33 or loss of CD45 contributes to impaired microglial clearance of amyloid beta and amyloid beta-induced loss of dendritic spines in microglial-neuronal co-cultures, aligning with a detrimental effect of CD33-mediated inhibition of CD45. CD33-CD45 interaction frequency was increased in monocytes from individuals with the rs3865444CC risk variant compared to rs3865444AA, as well as in AD compared to controls, independent of genotype. Furthermore, an interaction between CD33 and PTPRC (encoding CD45) gene expression in human brain tissue was associated with a pathological diagnosis of AD and global burden of AD pathology. Our findings thus establish a functional interaction between CD33 and CD45 relevant to AD susceptibility and systemic myeloid dysfunction in this disease.

neuroscience↗

CD33 and Clusterin Interact Biophysically and Genetically to Modulate Alzheimer Risk

We report the results of structural, functional and genetic studies on the CD33 sialic acid- binding receptor that reveal how non-coding variants in CD33 alter risk for Alzheimers disease (AD). The full-length CD33M isoform, whose expression is upregulated by non-coding AD-risk alleles, preferentially forms dimers at the cell surface, where they interact with AD-related proteins (clusterin and A{beta}). This interaction induces CD33M inhibitory signalling and downregulates protective microglial functions including phagocytic removal of amyloid plaques. Human brain expression quantitative trait loci (eQTL) and causal mediation analyses confirm that quantitative interactions between CLU and CD33 genotypes modulate AD phenotypes and suggest that genotypes at these loci might be used to personalise future therapeutic approaches. Our work also highlights several other unexpected aspects of CD33 biology, including a soluble shed extracellular fragment of CD33M and a similar soluble secreted product arising from a truncating mutation in the CD33 extracellular domain (CD33M{Delta}4bp).

neuroscience↗

APOE-ϵ4-induced Fibronectin at the blood-brain barrier is a conserved pathological mediator of disrupted astrocyte-endothelia interaction in Alzheimer's disease

Blood-brain barrier (BBB) dysfunction is a key feature of Alzheimers disease (AD), particularly in individuals carrying the APOE-{varepsilon}4 allele. This dysfunction worsens neuroinflammation and hinders the removal of toxic proteins, such as amyloid-beta (A{beta}42), from the brain. In post-mortem brain tissues and in animal models, we previously reported that fibronectin accumulates at the BBB predominantly in APOE-{varepsilon}4 carriers. Furthermore, we found a loss-of-function variant in the fibronectin 1 (FN1) gene significantly reduces aggregated fibronectin levels and decreases AD risk among APOE-{varepsilon}4 carriers. Yet, the molecular mechanisms downstream of fibronectin at the BBB remain unclear. The extracellular matrix (ECM) plays a crucial role in maintaining BBB homeostasis and orchestrating the interactions between BBB cell types, including endothelia and astrocytes. Understanding the mechanisms affecting the ECM and BBB cell types will be critical for developing effective therapies against AD, especially among APOE-{varepsilon}4 carriers. Here, we demonstrate that APOE-{varepsilon}4, A{beta}42, and inflammation drive the induction of FN1 expression in several models including zebrafish, mice, iPSC-derived human 3D astrocyte and 3D cerebrovascular cell cultures, and in human brains. Fibronectin accumulation disrupts astroglial-endothelial interactions and the signalling cascade between vascular endothelial growth factor (VEGF), heparin-binding epidermal growth factor (HBEGF) and Insulin-like growth factor 1 (IGF1). This accumulation of fibronectin in APOE-{varepsilon}4- associated AD potentiates BBB dysfunction, which strongly implicates reducing fibronectin deposition as a potential therapeutic target for AD. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=197 SRC="FIGDIR/small/634732v1_ufig1.gif" ALT="Figure 1"> View larger version (70K): org.highwire.dtl.DTLVardef@1efff03org.highwire.dtl.DTLVardef@14f40cdorg.highwire.dtl.DTLVardef@27743aorg.highwire.dtl.DTLVardef@3fa9a9_HPS_FORMAT_FIGEXP M_FIG C_FIG Accessibility textThis image illustrates the effects of different APOE isoforms (ApoE-{varepsilon}3 and ApoE-{varepsilon}4) on blood-brain barrier (BBB) integrity, focusing on the molecular interactions between astrocytes and endothelial cells. This figure emphasizes the detrimental effects of ApoE-{varepsilon}4 on BBB integrity via fibronectin accumulation and altered signaling pathways. The top section provides a schematic overview of the blood-brain barrier, highlighting astrocytes, endothelial cells, and their interface. The left panel represents the ApoE-{varepsilon}3 condition: Normal fibronectin (FN1) levels support healthy interactions between astrocytes and endothelial cells. Growth factors, including VEGFA, HBEGF, and IGF1, maintain BBB integrity through their respective receptors (VEGFR and EGFR). Green arrows indicate activation of these signaling pathways. The right panel depicts the ApoE-{varepsilon}4 condition: Elevated fibronectin (FN1) disrupts astrocyte-endothelium interactions. FN1 binds integrins and activates focal adhesion kinase (FAK), inhibiting VEGFA, which is required for endothelial HBEGF that in turn activates IGF1 signaling. Red symbols indicate inhibition of HBEGF, VEGFA, and IGF1 pathways, leading to BBB dysfunction. HighlightsAPOE-{varepsilon}4 drives fibronectin deposition in Alzheimers, disrupting astrocyte-endothelia interactions. APOE-{varepsilon}4 and fibronectin co-localize, forming aggregates at blood-brain barrier (BBB). Fibronectin alters the signaling between VEGF, IGF1, and HBEGF impairing BBB function. Reducing fibronectin restores BBB integrity and offsets APOE-{varepsilon}4 pathology.

cell biology↗

A Novel Gene ARHGAP44 for Longitudinal Changes in Glycated Hemoglobin (HbA1c) in Subjects without Type 2 Diabetes: Evidence from the Long Life Family Study (LLFS) and the Framingham Offspring Study (FOS)

Glycated hemoglobin (HbA1c) indicates average glucose levels over three months and is associated with insulin resistance and type 2 diabetes (T2D). Longitudinal changes in HbA1c ({Delta}HbA1c) are also associated with aging processes, cognitive performance, and mortality. We analyzed {Delta}HbA1c in 1,886 non-diabetic Europeans from the Long Life Family Study to uncover gene variants influencing {Delta}HbA1c. Using growth curve modeling adjusted for multiple covariates, we derived {Delta}HbA1c and conducted linkage-guided sequence analysis. Our genome-wide linkage scan identified a significant locus on 17p12. In-depth analysis of this locus revealed a variant rs56340929 (explaining 27% of the linkage peak) in the ARHGAP44 gene that was significantly associated with {Delta}HbA1c. RNA transcription of ARHGAP44 was associated with {Delta}HbA1c. The Framingham Offspring Study data further supported these findings on the gene level. Together, we found a novel gene ARHGAP44 for {Delta}HbA1c in family members without T2D. Follow-up studies using longitudinal omics data in large independent cohorts are warranted.

genetics↗

ABCA7-dependent Neuropeptide-Y signalling is a resilience mechanism required for synaptic integrity in Alzheimer's disease

Alzheimers disease (AD) remains a complex challenge characterized by cognitive decline and memory loss. Genetic variations have emerged as crucial players in the etiology of AD, enabling hope for a better understanding of the disease mechanisms; yet the specific mechanism of action for those genetic variants remain uncertain. Animal models with reminiscent disease pathology could uncover previously uncharacterized roles of these genes. Using CRISPR/Cas9 gene editing, we generated a knockout model for abca7, orthologous to human ABCA7 - an established AD-risk gene. The abca7+/- zebrafish showed reduced astroglial proliferation, synaptic density, and microglial abundance in response to amyloid beta 42 (A{beta}42). Single-cell transcriptomics revealed abca7-dependent neuronal and glial cellular crosstalk through neuropeptide Y (NPY) signaling. The abca7 knockout reduced the expression of npy, bdnf and ngfra, which are required for synaptic integrity and astroglial proliferation. With clinical data in humans, we showed reduced NPY in AD correlates with elevated Braak stage, predicted regulatory interaction between NPY and BDNF, identified genetic variants in NPY associated with AD, found segregation of variants in ABCA7, BDNF and NGFR in AD families, and discovered epigenetic changes in the promoter regions of NPY, NGFR and BDNF in humans with specific single nucleotide polymorphisms in ABCA7. These results suggest that ABCA7-dependent NPY signaling is required for synaptic integrity, the impairment of which generates a risk factor for AD through compromised brain resilience. O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/573893v1_ufig1.gif" ALT="Figure 1"> View larger version (73K): org.highwire.dtl.DTLVardef@eecf7forg.highwire.dtl.DTLVardef@78d8e0org.highwire.dtl.DTLVardef@1e65d71org.highwire.dtl.DTLVardef@100db01_HPS_FORMAT_FIGEXP M_FIG Graphical abstract C_FIG

neuroscience↗

Rare genetic variation in Fibronectin 1 (FN1) protects against APOEe4 in Alzheimer's disease

The risk of developing Alzheimers disease (AD) significantly increases in individuals carrying the APOE{varepsilon}4 allele. Elderly cognitively healthy individuals with APOE{varepsilon}4 also exist, suggesting the presence of cellular mechanisms that counteract the pathological effects of APOE{varepsilon}4; however, these mechanisms are unknown. We hypothesized that APOE{varepsilon}4 carriers without dementia might carry genetic variations that could protect them from developing APOE{varepsilon}4-mediated AD pathology. To test this, we leveraged whole genome sequencing (WGS) data in National Institute on Aging Alzheimers Disease Family Based Study (NIA-AD FBS), Washington Heights/Inwood Columbia Aging Project (WHICAP), and Estudio Familiar de Influencia Genetica en Alzheimer (EFIGA) cohorts and identified potentially protective variants segregating exclusively among unaffected APOE{varepsilon}4 carriers. In homozygous unaffected carriers above 70 years old, we identified 510 rare coding variants. Pathway analysis of the genes harboring these variants showed significant enrichment in extracellular matrix (ECM)-related processes, suggesting protective effects of functional modifications in ECM proteins. We prioritized two genes that were highly represented in the ECM-related gene ontology terms, (FN1) and collagen type VI alpha 2 chain (COL6A2) and are known to be expressed at the blood-brain barrier (BBB), for postmortem validation and in vivo functional studies. The FN1 and COL6A2 protein levels were increased at the BBB in APOE{varepsilon}4 carriers with AD. Brain expression of cognitively unaffected homozygous APOE{varepsilon}4 carriers had significantly lower FN1 deposition and less reactive gliosis compared to homozygous APOE{varepsilon}4 carriers with AD, suggesting that FN1 might be a downstream driver of APOE{varepsilon}4-mediated AD-related pathology and cognitive decline. To validate our findings, we used zebrafish models with loss-of-function (LOF) mutations in fn1b - the ortholog for human FN1. We found that fibronectin LOF reduced gliosis, enhanced gliovascular remodeling and potentiated the microglial response, suggesting that pathological accumulation of FN1 could impair toxic protein clearance, which is ameliorated with FN1 LOF. Our study suggests vascular deposition of FN1 is related to the pathogenicity of APOE{varepsilon}4, LOF variants in FN1 may reduce APOE{varepsilon}4-related AD risk, providing novel clues to potential therapeutic interventions targeting the ECM to mitigate AD risk.

genetics↗

Polygenic Risk Associated with Alzheimer's Disease and Other Traits Influences Genes Involved in T Cell Signaling and Activation

T cells, members of the adaptive immune system known for their ability to respond to an enormous variety of pathogens and other insults, are increasingly recognized as important mediators of pathology in neurodegeneration and other diseases. Previously, we and others have shown that T cell gene expression phenotypes are regulated by genetic variants associated with autoimmune disease, neurodegenerative disease, and inflammatory processes. However, many complex diseases have polygenic risk with thousands of common variants contributing a small amount to disease heritability. Here, we compute the polygenic risk score (PRS) of several autoimmune, neurological, and psychiatric disorders and present the first correlation of these PRSs with T cell gene expression, using transcriptomic and genomic sequencing data from a cohort of Alzheimers disease (AD) patients and age-matched controls. We validate our AD PRS against clinical metrics in our cohort and then compare PRS-associated genes across traits and four T cell subtypes. Several genes and biological pathways associated with the PRS for these traits relate to functions such as T cell chemotaxis, differentiation, response to and production of cytokines, and regulation of T cell receptor signaling. We also found that the trait-associated gene expression signature for certain traits was polarized towards a particular T cell subset, such as CD4+ for autoimmune disease traits or CD8+ for some psychiatric disease traits. Our findings may help guide efforts in precision medicine to target specific T cell functions in individuals with high polygenic risk for various complex diseases.

bioinformatics↗

ZCCHC17 modulates neuronal RNA splicing and supports cognitive resilience in Alzheimer's disease

ZCCHC17 is a putative master regulator of synaptic gene dysfunction in Alzheimers Disease (AD), and ZCCHC17 protein declines early in AD brain tissue, before significant gliosis or neuronal loss. Here, we investigate the function of ZCCHC17 and its role in AD pathogenesis. Co-immunoprecipitation of ZCCHC17 followed by mass spectrometry analysis in human iPSC-derived neurons reveals that ZCCHC17s binding partners are enriched for RNA splicing proteins. ZCCHC17 knockdown results in widespread RNA splicing changes that significantly overlap with splicing changes found in AD brain tissue, with synaptic genes commonly affected. ZCCHC17 expression correlates with cognitive resilience in AD patients, and we uncover an APOE4 dependent negative correlation of ZCCHC17 expression with tangle burden. Furthermore, a majority of ZCCHC17 interactors also co-IP with known tau interactors, and we find significant overlap between alternatively spliced genes in ZCCHC17 knockdown and tau overexpression neurons. These results demonstrate ZCCHC17s role in neuronal RNA processing and its interaction with pathology and cognitive resilience in AD, and suggest that maintenance of ZCCHC17 function may be a therapeutic strategy for preserving cognitive function in the setting of AD pathology. SignificanceAbnormal RNA processing is an important component of AD pathophysiology. We show here that ZCCHC17, a previously identified putative master regulator of synaptic dysfunction in AD, plays a role in neuronal RNA processing, and illustrate that ZCCHC17 dysfunction is sufficient to explain some of the splicing abnormalities seen in AD brain tissue, including synaptic gene splicing abnormalities. Using data from human patients, we demonstrate that ZCCHC17 mRNA levels correlate with cognitive resilience in the setting of AD pathology. These results suggest that maintenance of ZCCHC17 function may be a therapeutic strategy for supporting cognitive function in AD patients, and motivate future work examining a possible role of abnormal RNA processing in AD-related cognitive decline.

neuroscience↗

Cell-subtype specific effects of genetic variation in the aging and Alzheimer cortex

The relationship between genetic variation and gene expression in individual brain cell types and subtypes has remained elusive. Here, we generated single-nucleus RNA sequencing data from the dorsolateral prefrontal cortex of 424 individuals of advanced age; analyzing 1.5 million nuclear transcriptomes, we assessed the effect of genetic variants on RNA expression in cis (cis-eQTL) for 7 cell types and 81 cell subtypes. This effort identified 10,004 eGenes at the cell type level and 8,138 eGenes at the cell subtype level. Many eGenes are only detected within cell subtypes. A new variant influences APOE expression only in microglia and is associated with greater cerebral amyloid angiopathy but not Alzheimer pathology, accounting for the effect of APOE{varepsilon}4, providing mechanistic insights into both pathologies. While eQTLs are readily detected, only a TMEM106B variant robustly affects the proportion of cell subtypes. Integration of these results with GWAS highlighted the targeted cell type and likely causal gene within susceptibility loci for Alzheimers, Parkinsons, schizophrenia, and educational attainment.

genomics↗

Retrotransposons facilitates tissue specific horizontal Transfer of circulating tumor DNA

A variety of organisms have been shown to have altered physiology or developed pathology due to gene transfer, but mammals have never been shown to do so. Here, we show that circulating tumor DNA (ct) can promote cell-specific horizontal gene transfer (HGT) between human cancer cells and explain the mechanisms behind this phenomenon. Once ctDNA enters the host cell, it migrates to the nucleus and integrates into the cells genome, thereby transferring its genetic information. We determine that retrotransposons of the ERVL, SINE, and LINE families are necessary for cell targeting and the integration of ctDNA into host DNA. Using chemically synthesized retrotransposons, we found that AluSp and MER11C reproduced multiple myelomas (MM) ctDNAs cell targeting and integration into MM cells. We also discovered that ctDNA might, as a result of HGT, influence the treatment response of multiple myeloma and pancreatic cancer models. Overall, this is the first study to show that retrotransposon-directed HGT can promote genetic material transfer in cancer. There is, however, a broader impact of our findings than just cancer since cell-free DNA has also been found in physiological and other pathological conditions as well. Furthermore, with the discovery of transposons-mediated tissue-specific targeting, a new avenue for the delivery of genes and therapies will emerge.

cancer biology↗

A comparative study of structural variant calling strategies using the Alzheimer's Disease Sequencing Project's whole genome family data

BackgroundReliable detection and accurate genotyping of structural variants (SVs) and insertion/deletions (indels) from whole-genome sequence (WGS) data is a significant challenge. We present a protocol for variant calling, quality control, call merging, sensitivity analysis, in silico genotyping, and laboratory validation protocols for generating a high-quality deletion call set from whole genome sequences as part of the Alzheimers Disease Sequencing Project (ADSP). This dataset contains 578 individuals from 111 families. MethodsWe applied two complementary pipelines (Scalpel and Parliament) for SV/indel calling, break-point refinement, genotyping, and local reassembly to produce a high-quality annotated call set. Sensitivity was measured in sample replicates (N=9) for all callers using in silico variant spike-in for a wide range of event sizes. We focused on deletions because these events were more reliably called. To evaluate caller specificity, we developed a novel metric called the D-score that leverages deletion sharing frequencies within and outside of families to rank recurring deletions. Assessment of overall quality across size bins was measured with the kinship coefficient. Individual callers were evaluated for computational cost, performance, sensitivity, and specificity. Quality of calls were evaluated by Sanger sequencing of predicted loss-of-function (LOF) variants, variants near AD candidate genes, and randomly selected genome-wide deletions ranging from 2 to 17,000 bp. ResultsWe generated a high-quality deletion call set across a wide range of event sizes consisting of 152,301 deletions with an average of 263 per genome. A total of 114 of 146 predicted deletions (78.1%) were validated by Sanger sequencing. Scalpel was more accurate in calling deletions [≤]100 bp, whereas for Parliament, sensitivity was improved for deletions > 900 bp. We validated 83.0% (88/106) and 72.5% (37/51) of calls made by Scalpel and Parliament, respectively. Eleven deletions called by both Parliament and Scalpel in the 101-900 bin were tested and all were confirmed by Sanger sequencing. ConclusionsWe developed a flexible protocol to assess the quality of deletion detection across a wide range of sizes. We also generated a truth set of Sanger sequencing validated deletions with precise breakpoints covering a wide spectrum of sizes between 1 and 17,000 bp.

genetics↗

An Association Test of the Spatial Distribution of Rare Missense Variants within Protein Structures Improves Statistical Power of Sequencing Studies

Over 90% of variants are rare, and 50% of them are singletons in the Alzheimers Disease Sequencing Project Whole Exome Sequencing (ADSP WES) data. However, either single variant tests or unit-based tests are limited in the statistical power to detect the association between rare variants and phenotypes. To best utilize rare variants and investigate their biological effect, we exam their association with phenotypes in the context of protein. We developed a protein structure-based approach, POKEMON (Protein Optimized Kernel Evaluation of Missense Nucleotides), which evaluates rare missense variants based on their spatial distribution on the protein rather than allele frequency. The hypothesis behind this is that the three-dimensional spatial distribution of variants within a protein structure provides functional context and improves the power of association tests. POKEMON identified four candidate genes from the ADSP WES data, namely two known Alzheimers disease (AD) genes (TREM2 and SORL) and two novel genes (DUSP18 and CSF1R). For known AD genes, the signal from the spatial cluster is stable even if we exclude known AD risk variants, indicating the presence of additional low frequency risk variants within these genes. DUSP18 has a cluster of variants primarily shared by case subjects around the ligand-binding domain, and this cluster is further validated in a replication dataset with a larger sample size. POKEMON is an open-source tool available at https://github.com/bushlab-genomics/POKEMON.

bioinformatics↗

Rare variants imputation in admixed populations: Comparison across reference panels and bioinformatics tools.

BackgroundImputation has become a standard approach in genome-wide association studies (GWAS) to infer in silico untyped markers. Although feasibility for common variants imputation is well established, we aimed to assess rare and ultra-rare variants imputation in an admixed Caribbean Hispanic population (CH). MethodsWe evaluated imputation accuracy in CH (N = 1,000), focusing on rare (0.1% [&le;]minor allele frequency (MAF) [&le;] 1%) and ultra-rare (MAF < 0.1%) variants. We used two reference panels, the Haplotype Reference Consortium (HRC; N = 27,165) and 1000 Genome Project (1000G phase 3; N = 2,504) and multiple phasing (SHAPEIT, Eagle2) and imputation algorithms (IMPUTE2, MACH-Admix). To assess imputation quality, we reported: a) high-quality variant counts according to imputation tools internal indexes (e.g. IMPUTE2 "Info"[&ge;]80%). b) Wilcoxon Signed-Rank Test comparing imputation quality for genotyped variants that were masked and imputed; c) Cohens kappa coefficient to test agreement between imputed and whole-exome sequencing (WES) variants; d) imputation of G206A mutation in the PSEN1 (ultra-rare in the general population an more frequent in CH) followed by confirmation genotyping. We also tested ancestry proportion (European, African and Native American) against WES-imputation mismatches in a Poisson regression fashion. ResultsSHAPEIT2 retrieved higher percentage of imputed high-quality variants than Eagle2 (rare: 51.02% vs. 48.60%; ultra-rare 0.66% vs 0.65%, Wilcoxon p-value < 0.001). SHAPEIT-IMPUTE2 employing HRC outperformed 1000G (64.50% vs. 59.17%; 1.69% vs 0.75% for high-quality rare and ultra-rare variants, respectively; Wilcoxon p-value < 0.001). SHAPEIT-IMPUTE2 outperformed MaCH-Admix. Compared to 1000G, HRC-imputation retrieved a higher number of high-quality rare and ultra-rare variants, despite showing lower agreement between imputed and WES variants (e.g. rare: 98.86% for HRC vs. 99.02% for 1000G). High Kappa (K = 0.99) was observed for both reference panels. Twelve G206A mutation carriers were imputed and all validated by confirmation genotyping. African ancestry was associated with higher imputation errors for uncommon and rare variants (p-value < 1e-05). ConclusionReference panels with larger numbers of haplotypes can improve imputation quality for rare and ultra-rare variants in admixed populations such as CH. Ethnic composition is an important predictor of imputation accuracy, with higher African ancestry associated with poorer imputation accuracy.

bioinformatics↗

Quality Control and Integration of Genotypes from Two Calling Pipelines for Whole Genome Sequence Data in the Alzheimer’s Disease Sequencing Project

The Alzheimers Disease Sequencing Project (ADSP) performed whole genome sequencing (WGS) of 584 subjects from 111 multiplex families at three sequencing centers. Genotype calling of single nucleotide variants (SNVs) and insertion-deletion variants (indels) was performed centrally using GATK-HaplotypeCaller and Atlas V2. The ADSP Quality Control (QC) Working Group applied QC protocols to project-level variant call format files (VCFs) from each pipeline, and developed and implemented a novel protocol, termed \"consensus calling,\" to combine genotype calls from both pipelines into a single high-quality set. QC was applied to autosomal bi-allelic SNVs and indels, and included pipeline-recommended QC filters, variant-level QC, and sample-level QC. Low-quality variants or genotypes were excluded, and sample outliers were noted. Quality was assessed by examining Mendelian inconsistencies (MIs) among 67 parent-offspring pairs, and MIs were used to establish additional genotype-specific filters for GATK calls. After QC, 578 subjects remained. Pipeline-specific QC excluded ~12.0% of GATK and 14.5% of Atlas SNVs. Between pipelines, ~91% of SNV genotypes across all QCed variants were concordant; 4.23% and 4.56% of genotypes were exclusive to Atlas or GATK, respectively; the remaining ~0.01% of discordant genotypes were excluded. For indels, variant-level QC excluded ~36.8% of GATK and 35.3% of Atlas indels. Between pipelines, ~55.6% of indel genotypes were concordant; while 10.3% and 28.3% were exclusive to Atlas or GATK, respectively; and ~0.29% of discordant genotypes were. The final WGS consensus dataset contains 27,896,774 SNVs and 3,133,926 indels and is publicly available.\n\nAbbreviationsAD, Alzheimers disease; QC, Quality Control; LSSAC, Large-Scale Sequencing and Analysis Center; Broad, Broad Institute Genomics Service; Baylor, Baylor College of Medicine Human Genome Sequencing Center; WashU, Washington University-St. Louis McDonnell Genome Institute; WGS, whole genome sequencing; WES, whole exome sequencing; indel, insertion-deletion variants; VCF, variant control format; MI, Mendelian inconsistency; MC, Mendelian consistency; GWAS, genome-wide association study; VR, referent allele read depth; DP, overall read depth; MS, mapping score; GQ, genotype quality score; Ti/Tv, Transition/Transversion; CS, concordance code

genetics↗