Whole-genome sequencing reveals novel ethnicity-specific rare variants associated with Alzheimer's disease

Whole-genome sequencing analyses suggest novel genetic factors associated with Alzheimer's disease and a cumulative effects model for risk liability

Genome-wide association studies (GWAS) on Alzheimer's disease (AD) have predominantly focused on identifying common variants in Europeans. Here, we performed whole-genome sequencing (WGS) of 1,559 individuals from a Korean AD cohort to identify various genetic variants and biomarkers associated with AD. Our GWAS analysis identified a previously unreported locus for common variants (APCDD1) associated with AD. Our WGS analysis was extended to explore the less-characterized genetic factors contributing to AD risk. We identified rare noncoding variants located in cis-regulatory elements specific to excitatory neurons associated with cognitive impairment. Moreover, structural variation analysis showed that short tandem repeat expansion was associated with an increased risk of AD, and copy number variant at the HPSE2 locus showed borderline statistical significance. APOE ε4 carriers with high polygenic burden or structural variants exhibited severe cognitive impairment and increased amyloid beta levels, suggesting a cumulative effects model of AD risk.

Genetic Links Between Subcortical Brain Morphometry and Suicide Attempt Risk in Children and Adults

Genome-wide association studies (GWAS) have uncovered genetic variants associated with suicide attempt (SA) risk and regional brain volumes (RBVs). However, the extent of their genetic overlap remains unclear. To address this, we investigated whether the genetic architecture of SA and various RBVs (i.e., caudate nucleus, hippocampus, brainstem, ventral diencephalon, thalamus, globus pallidus, putamen, nucleus accumbens, amygdala and intracranial volume (ICV)) was shared. We leveraged GWAS summary statistics from the largest available datasets on SA (N = 958,896) and intracranial and subcortical RBVs (N = 74,898). Using linkage disequilibrium score regression, we estimated genome-wide genetic correlations between SA and individual RBVs. GWAS-pairwise analyses identified genomic segments associated with both SA and RBVs, followed by functional annotation. Additionally, we examined whether polygenic scores (PGS) for SA were associated with ICV and subcortical brain structure phenotypes in youth of European ancestry (N = 5276) in the Adolescent Brain Cognitive Development (ABCD) study. Linkage disequilibrium score regression results indicated a significant genetic correlation between SA and ICV (rG = -0.10, p-value = 1.9 × 10-3). GWAS-pairwise analyses and functional annotation revealed 10 genomic segments associated with SA and at least one RBV (thalamus, putamen and caudate nucleus). After adjusting for multiple tests, PGS association analysis indicated that a higher PGS for SA was significantly associated with a smaller volume of the right nucleus accumbens (b = -7.05, p = 0.018). Our findings highlight a negative genetic correlation between SA and ICV amongst adults and suggest different neural correlates associated with genetic risk for SA across developmental periods. This study advances our understanding of the shared genetic underpinnings of SA and brain structure, potentially informing future research and clinical interventions.

Navigating the blurred boundary: Neuropathologic changes versus clinical symptoms in Alzheimer's disease, and its consequences for research in genetics

During decades scientists tried to unveil the genetic architecture of Alzheimer's disease (AD), recurring to increasingly larger sample numbers for genome-wide association studies (GWAS) in hope for higher statistical gains. Here, a retrospective look on the most prominent GWAS was performed, focusing on the quality of the diagnosis associated with the used data and databases. Different methods for AD diagnosis (or absence) carry different levels of accuracy and certainty applied to both subsets of cases and controls. Furthermore, the different phenotypes included in these databases were explored, as several incorporate other ageing comorbidities and might be encompassing many confounding agents as well. Age of the samples' donors and origin populations were also investigated as these could be biasing factors in posterior analyses. A tendency for looser diagnostic methods in more recent GWAS was observed, where greater datasets of individuals are analyzed, which may have been hampering the discovery of associated genetic variants. Specifically for AD, a diagnostic method conveying a clinical outcome may be distinct from the disease neuropathological assessment, since the first has a practical perspective that not necessarily needs a confirmation. Due to its properties and complex diagnosis, this work highlights the importance of the neuropathological confirmation of AD (or its absence) in the subjects considered for research purposes to avoid reaching statistically weak and/or misleading conclusions that may trigger further studies with powerless groundwork.

A possible genetic predisposition to suspected hypoxic-ischaemic encephalopathy

Within the last decade, several studies have explored whether there might be a genetic component in hypoxic-ischaemic encephalopathy (HIE) that influences susceptibility to or outcomes following hypoxic-ischaemic injury. This review provides a comprehensive overview of the findings to date from published studies investigating the genetics of HIE. It also highlights some of the challenges faced by researchers, as well as recommendations for future research.

An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets

Although rare diseases (RDs) affect over 260 million individuals worldwide, low data quality and scarcity challenge effective care and research. This work aims to harmonise the Common Data Set by European Rare Disease Registry Infrastructure, Health Level 7 Fast Healthcare Interoperability Base Resources, and the Global Alliance for Genomics and Health Phenopacket Schema into a novel rare disease common data model (RD-CDM), laying the foundation for developing international RD-CDMs aligned with these data standards. We developed a modular-based GitHub repository and documentation to account for flexibility, extensions and further development. Recommendations on the model's cardinalities are given, inviting further refinement and international collaboration. An ontology-based approach was selected to find a common denominator between the semantic and syntactic data standards. Our RD-CDM version 2.0.0 comprises 78 data elements, extending the ERDRI-CDS by 62 elements with previous versions implemented in four German university hospitals capturing real world data for development and evaluation. We identified three categories for evaluation: Medical Data Granularity, Clinical Reasoning and Medical Relevance, and Interoperability and Harmonisation.

Integrating rare pathogenic variant prioritization with gene-based association analysis to identify novel genes and relevant multimodal traits for Alzheimer's disease

INTRODUCTION

Increasing evidence has highlighted rare variants in Alzheimer's disease (AD). However, insufficient sample sizes, especially in underrepresented ethnic groups, hinder their investigation. Additionally, their impact on endophenotypes remains largely unexplored.

METHODS

We prioritized rare likely-deleterious variants based on whole-genome sequencing data from a Chinese AD cohort (n = 988). Gene-based optimal sequence kernel association tests were conducted between AD cases and normal controls to identify AD-related genes. Network clustering, endophenotype association, and cellular experiments were conducted to evaluate their functional consequences.

RESULTS

We identified 11 novel AD candidate genes, which captured AD-related pathways and enhanced AD risk prediction performance. Key genes (RABEP1, VIPR1, RPL3L, and CABIN1) were linked to cognitive decline and brain atrophy. Experiments showed RABEP1 p.R845W inducing endocytosis dysregulation and exacerbating toxic amyloid β accumulation, underscoring its therapeutic potential.

DISCUSSION

Our findings highlighted the contributions of rare variants to AD and provided novel insights into AD therapeutics.

HIGHLIGHTS

Identified 11 novel AD candidate genes in a Chinese AD cohort. Correlated candidate genes with AD-related cognitive and brain imaging traits. Indicated RABEP1 p.R845W as a critical AD contributor in the endocytic pathway.

Fast and accurate DNASeq variant calling workflow composed of LUSH toolkit

BACKGROUND

Whole genome sequencing (WGS) is becoming increasingly prevalent for molecular diagnosis, staging and prognosis because of its declining costs and the ability to detect nearly all genes associated with a patient's disease. The currently widely accepted variant calling pipeline, GATK, is limited in terms of its computational speed and efficiency, which cannot meet the growing analysis needs.

RESULTS

Here, we propose a fast and accurate DNASeq variant calling workflow that is purely composed of tools from LUSH toolkit. The precision and recall measurements indicate that both the LUSH and GATK pipelines exhibit high levels of consistency, with precision and recall rates exceeding 99% on the 30x NA12878 dataset. In terms of processing speed, the LUSH pipeline outperforms the GATK pipeline, completing 30x WGS data analysis in just 1.6 h, which is approximately 17 times faster than GATK. Notably, the LUSH_HC tool completes the processing from BAM to VCF in just 12 min, which is around 76 times faster than GATK.

CONCLUSION

These findings suggest that the LUSH pipeline is a highly promising alternative to the GATK pipeline for WGS data analysis, with the potential to significantly improve bedside analysis of acutely ill patients, large-scale cohort data analysis, and high-throughput variant calling in crop breeding programs. Furthermore, the LUSH pipeline is highly scalable and easily deployable, allowing it to be readily applied to various scenarios such as clinical diagnosis and genomic research.

Investigating Causal Associations between the Gut Microbiota and Dementia: A Mendelian Randomization Study

Background: The causal association of specific gut microbiota with dementia remains incompletely understood. We aimed to access the causal relationships in which one or more gut microbiota account for dementia. Method: Using data from the MiBioGen and FinnGen consortia, we employed multiple Mendelian randomization (MR) approaches including two-sample MR (TSMR), multivariable MR (MVMR), and Bayesian model averaging MR to comprehensively evaluate the causal associations between 119 genera and dementia, and to prioritize the predominant bacterium. Result: We identified 21 genera that had causal effects on dementia and suggested Barnesiella (OR = 0.827, 95%CI = 0.722-0.948, marginal inclusion probability [MIP] = 0.464; model-averaged causal estimate [MACE] = -0.068) and Allisonella (OR = 0.770, 95%CI = 0.693-0.855, MIP = 0.898, MACE = -0.204) as the predominant genera for AD and all-cause dementia. Conclusions: These findings confirm the causal relationships between specific gut microbiota and dementia, highlighting the necessity of multiple MR approaches in gut microbiota analysis, and provides promising genera as potential novel biomarkers for dementia risk.

GRPa-PRS: A risk stratification method to identify genetically-regulated pathways in polygenic diseases

Background

Polygenic risk scores (PRS) are tools used to evaluate an individual's susceptibility to polygenic diseases based on their genetic profile. A considerable proportion of people carry a high genetic risk but evade the disease. On the other hand, some individuals with a low risk of eventually developing the disease. We hypothesized that unknown counterfactors might be involved in reversing the PRS prediction, which might provide new insights into the pathogenesis, prevention, and early intervention of diseases.

Methods

We built a novel computational framework to identify genetically-regulated pathways (GRPas) using PRS-based stratification for each cohort. We curated two AD cohorts with genotyping data; the discovery (disc) and the replication (rep) datasets include 2722 and 2854 individuals, respectively. First, we calculated the optimized PRS model based on the three recent AD GWAS summary statistics for each cohort. Then, we stratified the individuals by their PRS and clinical diagnosis into six biologically meaningful PRS strata, such as AD cases with low/high risk and cognitively normal (CN) with low/high risk. Lastly, we imputed individual genetically-regulated expression (GReX) and identified differential GReX and GRPas between risk strata using gene-set enrichment and variational analyses in two models, with and without APOE effects. An orthogonality test was further conducted to verify those GRPas are independent of PRS risk. To verify the generalizability of other polygenic diseases, we further applied a default model of GRPa-PRS for schizophrenia (SCZ).

Results

For each stratum, we conducted the same procedures in both the disc and rep datasets for comparison. In AD, we identified several well-known AD-related pathways, including amyloid-beta clearance, tau protein binding, and astrocyte response to oxidative stress. Additionally, we discovered resilience-related GRPs that are orthogonal to AD PRS, such as the calcium signaling pathway and divalent inorganic cation homeostasis. In SCZ, pathways related to mitochondrial function and muscle development were highlighted. Finally, our GRPa-PRS method identified more consistent differential pathways compared to another variant-based pathway PRS method.

Conclusions

We developed a framework, GRPa-PRS, to systematically explore the differential GReX and GRPas among individuals stratified by their estimated PRS. The GReX-level comparison among those strata unveiled new insights into the pathways associated with disease risk and resilience. Our framework is extendable to other polygenic complex diseases.

Whole genome-wide sequence analysis of long-lived families (Long-Life Family Study) identifies MTUS2 gene associated with late-onset Alzheimer's disease

INTRODUCTION

Late-onset Alzheimer's disease (LOAD) has a strong genetic component. Participants in Long-Life Family Study (LLFS) exhibit delayed onset of dementia, offering a unique opportunity to investigate LOAD genetics.

METHODS

We conducted a whole genome sequence analysis of 3475 LLFS members. Genetic associations were examined in six independent studies (N = 14,260) with a wide range of LOAD risk. Association analysis in a sub-sample of the LLFS cohort (N = 1739) evaluated the association of LOAD variants with beta amyloid (Aβ) levels.

RESULTS

We identified several single nucleotide polymorphisms (SNPs) in tight linkage disequilibrium within the MTUS2 gene associated with LOAD (rs73154407, p = 7.6 × 10-9). Association of MTUS2 variants with LOAD was observed in the five independent studies and was significantly stronger within high levels of Aβ42/40 ratio compared to lower amyloid.

DISCUSSION

MTUS2 encodes a microtubule associated protein implicated in the development and function of the nervous system, making it a plausible candidate to investigate LOAD biology.

HIGHLIGHTS

Long-Life Family Study (LLFS) families may harbor late onset Alzheimer's dementia (LOAD) variants. LLFS whole genome sequence analysis identified MTUS2 gene variants associated with LOAD. The observed LLFS variants generalized to cohorts with wide range of LOAD risk. The association of MTUS2 with LOAD was stronger within high levels of beta amyloid. Our results provide evidence for MTUS2 gene as a novel LOAD candidate locus.

The HLA-DRB1*09:01-DQB1*03:03 haplotype is associated with the risk for late-onset Alzheimer's disease in APOE ε 4-negative Japanese adults

Late-onset Alzheimer's disease (LOAD) is the most common cause of dementia among those older than 65 years. The onset of LOAD is influenced by neuroinflammation. The human leukocyte antigen (HLA) system is involved in regulating inflammatory responses. Numerous HLA alleles and their haplotypes have shown varying associations with LOAD in diverse populations, yet their impact on the Japanese population remains to be elucidated. Here, we conducted a comprehensive investigation into the associations between LOAD and HLA alleles within the Japanese population. Using whole-genome sequencing (WGS) data from 303 LOAD patients and 1717 cognitively normal (CN) controls, we identified four-digit HLA class I alleles (A, B, and C) and class II alleles (DRB1, DQB1, and DPB1). We found a significant association between the HLA-DRB1*09:01-DQB1*03:03 haplotype and LOAD risk in APOEε 4-negative samples (odds ratio = 1.81, 95% confidence interval = 1.38-2.38, P = 2.03× 10 − 5 ). These alleles not only showed distinctive frequencies specific to East Asians but demonstrated a high degree of linkage disequilibrium in APOEε 4-negative samples (r2 = 0.88). Because HLA class II molecules interact with T-cell receptors (TCRs), we explored potential disparities in the diversities of TCR α chain (TRA) and β chain (TRB) repertoires between APOEε 4-negative LOAD and CN samples. Lower diversity of TRA repertoires was associated with LOAD in APOEε 4-negative samples, irrespective of the HLA DRB1*09:01-DQB1*03:03 haplotype. Our study enhances the understanding of the etiology of LOAD in the Japanese population and provides new insights into the underlying mechanisms of its pathogenesis.

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.

Co-Expression Network Analysis Identifies Molecular Determinants of Loneliness Associated with Neuropsychiatric and Neurodegenerative Diseases

Loneliness and social isolation are detrimental to mental health and may lead to cognitive impairment and neurodegeneration. Although several molecular signatures of loneliness have been identified, the molecular mechanisms by which loneliness impacts the brain remain elusive. Here, we performed a bioinformatics approach to untangle the molecular underpinnings associated with loneliness. Co-expression network analysis identified molecular 'switches' responsible for dramatic transcriptional changes in the nucleus accumbens of individuals with known loneliness. Loneliness-related switch genes were enriched in cell cycle, cancer, TGF-β, FOXO, and PI3K-AKT signaling pathways. Analysis stratified by sex identified switch genes in males with chronic loneliness. Male-specific switch genes were enriched in infection, innate immunity, and cancer-related pathways. Correlation analysis revealed that loneliness-related switch genes significantly overlapped with 82% and 68% of human studies on Alzheimer's (AD) and Parkinson's diseases (PD), respectively, in gene expression databases. Loneliness-related switch genes, BCAM, NECTIN2, NPAS3, RBM38, PELI1, DPP10, and ASGR2, have been identified as genetic risk factors for AD. Likewise, switch genes HLA-DRB5, ALDOA, and GPNMB are known genetic loci in PD. Similarly, loneliness-related switch genes overlapped in 70% and 64% of human studies on major depressive disorder and schizophrenia, respectively. Nine switch genes, HLA-DRB5, ARHGAP15, COL4A1, RBM38, DMD, LGALS3BP, WSCD2, CYTH4, and CNTRL, overlapped with known genetic variants in depression. Seven switch genes, NPAS3, ARHGAP15, LGALS3BP, DPP10, SMYD3, CPXCR1, and HLA-DRB5 were associated with known risk factors for schizophrenia. Collectively, we identified molecular determinants of loneliness and dysregulated pathways in the brain of non-demented adults. The association of switch genes with known risk factors for neuropsychiatric and neurodegenerative diseases provides a molecular explanation for the observed prevalence of these diseases among lonely individuals.

Design, synthesis and bioevaluation of 1,2,4-thiadiazolidine-3,5-dione derivatives as potential GSK-3β inhibitors for the treatment of Alzheimer's disease

Tideglusib is a non-competitive GSK-3β inhibitor which contain 1,2,4-thiadiazolidine-3,5-dione moiety, and now mainly used for progressive supranuclear palsy due to the lack of some primary cognitive endpoints and secondary endpoints in a phase IIb trail for Alzheimer's disease. Additionally, insufficient evidence exists to support that there are obvious covalent bonds between Tideglusib and GSK-3β. Targeted covalent inhibition strategy could improve the binding efficiency, selectivity and duration of kinase inhibitors. Based on the above premise, two series of targeted compounds with acryloyl warheads were designed and synthesized. The kinase inhibitory activity of the selected compound 10a with better neuroprotective effect improved 2.7 fold than that of Tideglusib. After the preliminary screening of GSK-3β inhibition and neuroprotective activity, the mechanism action of the selected compound 10a was investigated in vitro and in vivo. The results confirmed that 10a with excellent selectivity among the whole tested kinases could significantly reduce the expressions of APP and p-Tau via increasing the level of p-GSK-3β. The pharmacodynamic assay in vivo showed that 10a could markedly improve the learning and memory functions in AD mice induced by AlCl₃ combined with d-galactose. At the same time, the damage of hippocampal neurons in AD mice was obviously reduced. Accordingly, the introduction of acryloyl warheads could increase the GSK-3β inhibitory activity of 1,2,4-thiadiazolidine-3,5-dione derivatives, and the selected compound 10a deserves further research as an effective GSK-3β inhibitor for the potential treatment of AD.

Alzheimer's Disease: An Updated Overview of Its Genetics

Alzheimer's disease (AD) is the most common neurodegenerative disease in the world. It is classified as familial and sporadic. The dominant familial or autosomal presentation represents 1-5% of the total number of cases. It is categorized as early onset (EOAD; <65 years of age) and presents genetic mutations in presenilin 1 (PSEN1), presenilin 2 (PSEN2), or the Amyloid precursor protein (APP). Sporadic AD represents 95% of the cases and is categorized as late-onset (LOAD), occurring in patients older than 65 years of age. Several risk factors have been identified in sporadic AD; aging is the main one. Nonetheless, multiple genes have been associated with the different neuropathological events involved in LOAD, such as the pathological processing of Amyloid beta (Aβ) peptide and Tau protein, as well as synaptic and mitochondrial dysfunctions, neurovascular alterations, oxidative stress, and neuroinflammation, among others. Interestingly, using genome-wide association study (GWAS) technology, many polymorphisms associated with LOAD have been identified. This review aims to analyze the new genetic findings that are closely related to the pathophysiology of AD. Likewise, it analyzes the multiple mutations identified to date through GWAS that are associated with a high or low risk of developing this neurodegeneration. Understanding genetic variability will allow for the identification of early biomarkers and opportune therapeutic targets for AD.

Omics-based biomarkers discovery for Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disorders presenting with the pathological hallmarks of amyloid plaques and tau tangles. Over the past few years, great efforts have been made to explore reliable biomarkers of AD. High-throughput omics are a technology driven by multiple levels of unbiased data to detect the complex etiology of AD, and it provides us with new opportunities to better understand the pathophysiology of AD and thereby identify potential biomarkers. Through revealing the interaction networks between different molecular levels, the ultimate goal of multi-omics is to improve the diagnosis and treatment of AD. In this review, based on the current AD pathology and the current status of AD diagnostic biomarkers, we summarize how genomics, transcriptomics, proteomics and metabolomics are all conducing to the discovery of reliable AD biomarkers that could be developed and used in clinical AD management.

Identification of potential blood biomarkers for early diagnosis of Alzheimer’s disease through immune landscape analysis

Mild cognitive impairment (MCI) is a clinical precursor of Alzheimer’s disease (AD). Recent genetic studies have reported on associations between AD risk genes and immunity. Here, we obtained samples and data from 317 AD, 432 MCI, and 107 cognitively normal (CN) subjects and investigated immune-cell type composition and immune clonal diversity of T-cell receptor (TRA, TRB, TRG, and TRD) and B-cell receptor (IGH, IGK, and IGL) repertoires through bulk RNA sequencing. We found the proportions of plasma cells, γδ T cells, neutrophils, and B cells were significantly different and the diversities of IGH, IGK, and TRA were significantly small with AD progression. We then identified a differentially expressed gene, WDR37, in terms of risk of MCI-to-AD conversion. Our prognosis prediction model using the potential blood-based biomarkers for early AD diagnosis, which combined two immune repertoires (IGK and TRA), WDR37, and clinical information, successfully classified MCI patients into two groups, low and high, in terms of risk of MCI-to-AD conversion (log-rank test P = 2.57e-3). It achieved a concordance index of 0.694 in a discovery cohort and of 0.643 in an independent validation cohort. We believe that further investigation, using larger sample sizes, will lead to practical clinical use in the near future.

Detection of Indiscriminate Genetic Manipulation in Thoroughbred Racehorses by Targeted Resequencing for Gene-Doping Control

The creation of genetically modified horses is prohibited in horse racing as it falls under the banner of gene doping. In this study, we developed a test to detect gene editing based on amplicon sequencing using next-generation sequencing (NGS). We designed 1012 amplicons to target 52 genes (481 exons) and 147 single-nucleotide variants (SNVs). NGS analyses showed that 97.7% of the targeted exons were sequenced to sufficient coverage (depth > 50) for calling variants. The targets of artificial editing were defined as homozygous alternative (HomoALT) and compound heterozygous alternative (ALT1/ALT2) insertion/deletion (INDEL) mutations in this study. Four models of gene editing (three homoALT with 1-bp insertions, one REF/ALT with 77-bp deletion) were constructed by editing the myostatin gene in horse fibroblasts using CRISPR/Cas9. The edited cells and 101 samples from thoroughbred horses were screened using the developed test, which was capable of identifying the three homoALT cells containing 1-bp insertions. Furthermore, 147 SNVs were investigated for their utility in confirming biological parentage. Of these, 120 SNVs were amenable to consistent and accurate genotyping. Surrogate (nonbiological) dams were excluded by 9.8 SNVs on average, indicating that the 120 SNV could be used to detect foals that have been produced by somatic cloning or embryo transfer, two practices that are prohibited in thoroughbred racing and breeding. These results indicate that gene-editing tests that include variant calling and SNV genotyping are useful to identify genetically modified racehorses.

Familial Early-Onset Alzheimer's Caused by Novel Genetic Variant and APP Duplication: A Cross-Sectional Study

BACKGROUND

The clinical characteristics of symptomatic and asymptomatic carriers of early- onset autosomal dominant Alzheimer's (EOADAD) due to a yet-undescribed chromosomal rearrangement may add to the available body of knowledge about Alzheimer's disease and may enlighten novel and modifier genes. We report the clinical and genetic characteristics of asymptomatic and symptomatic individuals carrying a novel APP duplication rearrangement.

METHODS

Individuals belonging to a seven-generation pedigree with familial cognitive decline or intracerebral hemorrhages were recruited. Participants underwent medical, neurological, and neuropsychological evaluations. The genetic analysis included chromosomal microarray, Karyotype, fluorescence in situ hybridization, and whole genome sequencing.

RESULTS

Of 68 individuals, six females presented with dementia, and four males presented with intracerebral hemorrhage. Of these, nine were found to carry Chromosome 21 copy number gain (chr21:27,224,097-27,871,284, GRCh37/hg19) including the APP locus (APP-dup). In seven, Chromosome 5 copy number gain (Chr5: 24,786,234-29,446,070, GRCh37/hg19) (Chr5-CNG) cosegregated with the APP-dup. Both duplications co-localized to chromosome 18q21.1 and segregated in 25 pre-symptomatic carriers. Compared to non-carriers, asymptomatic carriers manifested cognitive decline in their mid-thirties. A third of the affected individuals carried a diagnosis of a dis-immune condition.

CONCLUSION

APP extra dosage, even in isolation and when located outside chromosome 21, is pathogenic. The clinical presentation of APP duplication varies and may be gender specific, i.e., ICH in males and cognitive-behavioral deterioration in females. The association with immune disorders is presently unclear but may prove relevant. The implication of Chr5-CNG co-segregation and the surrounding chromosome 18 genetic sequence needs further clarification.