A genome-wide association study identifies a locus associated with knee extension strength in older Japanese individuals.

Sarcopenia is a common skeletal muscle disease in older people. Lower limb muscle strength is a good predictive value for sarcopenia; however, little is known about its genetic components. Here, we conducted a genome-wide association study (GWAS) for knee extension strength in a total of 3452 Japanese aged 60 years or older from two independent cohorts. We identified a significant locus, rs10749438 which is an intronic variant in TACC2 (transforming acidic coiled-coil-containing 2) (P = 4.2 × 10-8). TACC2, encoding a cytoskeleton-related protein, is highly expressed in skeletal muscle, and is reported as a target of myotonic dystrophy 1-associated splicing alterations. These suggest that changes in TACC2 expression are associated with variations in muscle strength in older people. The association was consistently observed in young and middle-aged subjects. Our findings would shed light on genetic components of lower limb muscle strength and indicate TACC2 as a potential therapeutic target for sarcopenia.

Molecular subtypes of lung adenocarcinoma present distinct immune tumor microenvironments.

Overcoming resistance to immune checkpoint inhibitors is an important issue in patients with non-small-cell lung cancer (NSCLC). Transcriptome analysis shows that adenocarcinoma can be divided into three molecular subtypes: terminal respiratory unit (TRU), proximal proliferative (PP), and proximal inflammatory (PI), and squamous cell carcinoma (LUSQ) into four. However, the immunological characteristics of these subtypes are not fully understood. In this study, we investigated the immune landscape of NSCLC tissues in molecular subtypes using a multi-omics dataset, including tumor-infiltrating leukocytes (TILs) analyzed using flow cytometry, RNA sequences, whole exome sequences, metabolomic analysis, and clinicopathologic findings. In the PI subtype, the number of TILs increased and the immune response in the tumor microenvironment (TME) was activated, as indicated by high levels of tertiary lymphoid structures, and high cytotoxic marker levels. Patient prognosis was worse in the PP subtype than in other adenocarcinoma subtypes. Glucose transporter 1 (GLUT1) expression levels were upregulated and lactate accumulated in the TME of the PP subtype. This could lead to the formation of an immunosuppressive TME, including the inactivation of antigen-presenting cells. The TRU subtype had low biological malignancy and "cold" tumor-immune phenotypes. Squamous cell carcinoma (LUSQ) did not show distinct immunological characteristics in its respective subtypes. Elucidation of the immune characteristics of molecular subtypes could lead to the development of personalized immune therapy for lung cancer. Immune checkpoint inhibitors could be an effective treatment for the PI subtype. Glycolysis is a potential target for converting an immunosuppressive TME into an antitumorigenic TME in the PP subtype.

Identification of Potential Blood-Based Biomarkers for Frailty by Using an Integrative Approach.

INTRODUCTION: Although frailty is a geriatric syndrome that is associated with disability, hospitalization, and mortality, it can be reversible and preventable with the appropriate interventions. Additionally, as the current diagnostic criteria for frailty include only physical, psychological, cognitive, and social measurements, there is a need for promising blood-based molecular biomarkers to aid in the diagnosis of frailty. METHODS: To identify candidate blood-based biomarkers that can enhance current diagnosis of frailty, we conducted a comprehensive analysis of clinical data, messenger RNA-sequencing (RNA-seq), and aging-related factors using a total of 104 older adults aged 65-90 years (61 frail subjects and 43 robust subjects) in a cross-sectional case-control study. RESULTS: We identified two candidate biomarkers of frailty from the clinical data analysis, nine from the RNA-seq analysis, and six from the aging-related factors analysis. By using combinations of the candidate biomarkers and clinical information, we constructed risk prediction models. The best models used combinations that included skeletal muscle mass index measured by dual-energy X-ray absorptiometry (adjusted p = 0.026), GDF15 (adjusted p = 1.46E-03), adiponectin (adjusted p = 0.012), CXCL9 (adjusted p = 0.011), or apelin (adjusted p = 0.020) as the biomarker. These models achieved a high area under the curve of 0.95 in an independent validation cohort (95% confidence interval: 0.79-0.97). Our risk prediction models showed significantly higher areas under the curve than did models constructed using only basic clinical information (Welch's t test p < 0.001). CONCLUSION: All five biomarkers showed statistically significant correlations with components of the frailty diagnostic criteria. We discovered several potential biomarkers for the diagnosis of frailty. Further refinement may lead to their future clinical use.

Polygenic effects on the risk of Alzheimer's disease in the Japanese population.

BACKGROUND: Polygenic effects have been proposed to account for some disease phenotypes; these effects are calculated as a polygenic risk score (PRS). This score is correlated with Alzheimer's disease (AD)-related phenotypes, such as biomarker abnormalities and brain atrophy, and is associated with conversion from mild cognitive impairment (MCI) to AD. However, the AD PRS has been examined mainly in Europeans, and owing to differences in genetic structure and lifestyle, it is unclear whether the same relationships between the PRS and AD-related phenotypes exist in non-European populations. In this study, we calculated and evaluated the AD PRS in Japanese individuals using genome-wide association study (GWAS) statistics from Europeans. METHODS: In this study, we calculated the AD PRS in 504 Japanese participants (145 cognitively unimpaired (CU) participants, 220 participants with late mild cognitive impairment (MCI), and 139 patients with mild AD dementia) enrolled in the Japanese Alzheimer's Disease Neuroimaging Initiative (J-ADNI) project. In order to evaluate the clinical value of this score, we (1) determined the polygenic effects on AD in the J-ADNI and validated it using two independent cohorts (a Japanese neuropathology (NP) cohort (n = 565) and the North American ADNI (NA-ADNI) cohort (n = 617)), (2) examined the AD-related phenotypes associated with the PRS, and (3) tested whether the PRS helps predict the conversion of MCI to AD. RESULTS: The PRS using 131 SNPs had an effect independent of APOE. The PRS differentiated between CU participants and AD patients with an area under the curve (AUC) of 0.755 when combined with the APOE variants. Similar AUC was obtained when PRS calculated by the NP and NA-ADNI cohorts was applied. In MCI patients, the PRS was associated with cerebrospinal fluid phosphorylated-tau levels (ß estimate = 0.235, p value = 0.026). MCI with a high PRS showed a significantly increased conversion to AD in APOE ε4 noncarriers with a hazard rate of 2.22. In addition, we also developed a PRS model adjusted for LD and observed similar results. CONCLUSIONS: We showed that the AD PRS is useful in the Japanese population, whose genetic structure is different from that of the European population. These findings suggest that the polygenicity of AD is partially common across ethnic differences.

The HLA-DRB1*09:01-DQB1*03:03 haplotype is associated with the risk for late-onset Alzheimer's disease in APOE [Formula: see text]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 APOE [Formula: see text]4-negative samples (odds ratio = 1.81, 95% confidence interval = 1.38-2.38, P = 2.03[Formula: see text]). These alleles not only showed distinctive frequencies specific to East Asians but demonstrated a high degree of linkage disequilibrium in APOE [Formula: see text]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 ß chain (TRB) repertoires between APOE [Formula: see text]4-negative LOAD and CN samples. Lower diversity of TRA repertoires was associated with LOAD in APOE [Formula: see text]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.

Exploring the genetic diversity of the Japanese population: Insights from a large-scale whole genome sequencing analysis.

The Japanese archipelago is a terminal location for human migration, and the contemporary Japanese people represent a unique population whose genomic diversity has been shaped by multiple migrations from Eurasia. We analyzed the genomic characteristics that define the genetic makeup of the modern Japanese population from a population genetics perspective from the genomic data of 9,287 samples obtained by high-coverage whole-genome sequencing (WGS) by the National Center Biobank Network. The dataset comprised populations from the Ryukyu Islands and other parts of the Japanese archipelago (Hondo). The Hondo population underwent two episodes of population decline during the Jomon period, corresponding to the Late Neolithic, and the Edo period, corresponding to the Early Modern era, while the Ryukyu population experienced a population decline during the shell midden period of the Late Neolithic in this region. Haplotype analysis suggested increased allele frequencies for genes related to alcohol and fatty acid metabolism, which were reported as loci that had experienced positive natural selection. Two genes related to alcohol metabolism were found to be 12,500 years out of phase with the time when they began to increase in the allele frequency; this finding indicates that the genomic diversity of Japanese people has been shaped by events closely related to agriculture and food production.

Natural Selection Signatures in the Hondo and Ryukyu Japanese Subpopulations.

Natural selection signatures across Japanese subpopulations are under-explored. Here we conducted genome-wide selection scans with 622,926 single nucleotide polymorphisms for 20,366 Japanese individuals, who were recruited from the main-islands of Japanese Archipelago (Hondo) and the Ryukyu Archipelago (Ryukyu), representing two major Japanese subpopulations. The integrated haplotype score (iHS) analysis identified several signals in one or both subpopulations. We found a novel candidate locus at IKZF2, especially in Ryukyu. Significant signals were observed in the major histocompatibility complex region in both subpopulations. The lead variants differed and demonstrated substantial allele frequency differences between Hondo and Ryukyu. The lead variant in Hondo tags HLA-A*33:03-C*14:03-B*44:03-DRB1*13:02-DQB1*06:04-DPB1*04:01, a haplotype specific to Japanese and Korean. While in Ryukyu, the lead variant tags DRB1*15:01-DQB1*06:02, which had been recognized as a genetic risk factor for narcolepsy. In contrast, it is reported to confer protective effects against type 1 diabetes and human T lymphotropic virus type 1-associated myelopathy/tropical spastic paraparesis. The FastSMC analysis identified 8 loci potentially affected by selection within the past 20-150 generations, including 2 novel candidate loci. The analysis also showed differences in selection patterns of ALDH2 between Hondo and Ryukyu, a gene recognized to be specifically targeted by selection in East Asian. In summary, our study provided insights into the selection signatures within the Japanese and nominated potential sources of selection pressure.

Genetic insights into ossification of the posterior longitudinal ligament of the spine.

Ossification of the posterior longitudinal ligament of the spine (OPLL) is an intractable disease leading to severe neurological deficits. Its etiology and pathogenesis are primarily unknown. The relationship between OPLL and comorbidities, especially type 2 diabetes (T2D) and high body mass index (BMI), has been the focus of attention; however, no trait has been proven to have a causal relationship. We conducted a meta-analysis of genome-wide association studies (GWASs) using 22,016 Japanese individuals and identified 14 significant loci, 8 of which were previously unreported. We then conducted a gene-based association analysis and a transcriptome-wide Mendelian randomization approach and identified three candidate genes for each. Partitioning heritability enrichment analyses observed significant enrichment of the polygenic signals in the active enhancers of the connective/bone cell group, especially H3K27ac in chondrogenic differentiation cells, as well as the immune/hematopoietic cell group. Single-cell RNA sequencing of Achilles tendon cells from a mouse Achilles tendon ossification model confirmed the expression of genes in GWAS and post-GWAS analyses in mesenchymal and immune cells. Genetic correlations with 96 complex traits showed positive correlations with T2D and BMI and a negative correlation with cerebral aneurysm. Mendelian randomization analysis demonstrated a significant causal effect of increased BMI and high bone mineral density on OPLL. We evaluated the clinical images in detail and classified OPLL into cervical, thoracic, and the other types. GWAS subanalyses identified subtype-specific signals. A polygenic risk score for BMI demonstrated that the effect of BMI was particularly strong in thoracic OPLL. Our study provides genetic insight into the etiology and pathogenesis of OPLL and is expected to serve as a basis for future treatment development.

Trans-ethnic genomic informed risk assessment for Alzheimer's disease: An International Hundred K+ Cohorts Consortium study.

BACKGROUND: As a collaboration model between the International HundredK+ Cohorts Consortium (IHCC) and the Davos Alzheimer's Collaborative (DAC), our aim was to develop a trans-ethnic genomic informed risk assessment (GIRA) algorithm for Alzheimer's disease (AD). METHODS: The GIRA model was created to include polygenic risk score calculated from the AD genome-wide association study loci, the apolipoprotein E haplotypes, and non-genetic covariates including age, sex, and the first three principal components of population substructure. RESULTS: We validated the performance of the GIRA model in different populations. The proteomic study in the participant sites identified proteins related to female infertility and autoimmune thyroiditis and associated with the risk scores of AD. CONCLUSIONS: As the initial effort by the IHCC to leverage existing large-scale datasets in a collaborative setting with DAC, we developed a trans-ethnic GIRA for AD with the potential of identifying individuals at high risk of developing AD for future clinical applications.

Tumor-infiltrating Leukocyte Profiling Defines Three Immune Subtypes of NSCLC with Distinct Signaling Pathways and Genetic Alterations.

Resistance to immune checkpoint blockade remains challenging in patients with non-small cell lung cancer (NSCLC). Tumor-infiltrating leukocyte (TIL) quantity, composition, and activation status profoundly influence responsiveness to cancer immunotherapy. This study examined the immune landscape in the NSCLC tumor microenvironment by analyzing TIL profiles of 281 fresh resected NSCLC tissues. Unsupervised clustering based on numbers and percentages of 30 TIL types classified adenocarcinoma (LUAD) and squamous cell carcinoma (LUSQ) into the cold, myeloid cell-dominant, and CD8+ T cell-dominant subtypes. These were significantly correlated with patient prognosis; the myeloid cell subtype had worse outcomes than the others. Integrated genomic and transcriptomic analyses, including RNA sequencing, whole-exome sequencing, T-cell receptor repertoire, and metabolomics of tumor tissue, revealed that immune reaction-related signaling pathways were inactivated, while the glycolysis and K-ras signaling pathways activated in LUAD and LUSQ myeloid cell subtypes. Cases with ALK and ROS1 fusion genes were enriched in the LUAD myeloid subtype, and the frequency of TERT copy-number variations was higher in LUSQ myeloid subtype than in the others. These classifications of NSCLC based on TIL status may be useful for developing personalized immune therapies for NSCLC. Significance: The precise TIL profiling classified NSCLC into novel three immune subtypes that correlates with patient outcome, identifying subtype-specific molecular pathways and genomic alterations that should play important roles in constructing subtype-specific immune tumor microenvironments. These classifications of NSCLC based on TIL status are useful for developing personalized immune therapies for NSCLC.

Classification and deep-learning-based prediction of Alzheimer disease subtypes by using genomic data.

Late-onset Alzheimer's disease (LOAD) is the most common multifactorial neurodegenerative disease among elderly people. LOAD is heterogeneous, and the symptoms vary among patients. Genome-wide association studies (GWAS) have identified genetic risk factors for LOAD but not for LOAD subtypes. Here, we examined the genetic architecture of LOAD based on Japanese GWAS data from 1947 patients and 2192 cognitively normal controls in a discovery cohort and 847 patients and 2298 controls in an independent validation cohort. Two distinct groups of LOAD patients were identified. One was characterized by major risk genes for developing LOAD (APOC1 and APOC1P1) and immune-related genes (RELB and CBLC). The other was characterized by genes associated with kidney disorders (AXDND1, FBP1, and MIR2278). Subsequent analysis of albumin and hemoglobin values from routine blood test results suggested that impaired kidney function could lead to LOAD pathogenesis. We developed a prediction model for LOAD subtypes using a deep neural network, which achieved an accuracy of 0.694 (2870/4137) in the discovery cohort and 0.687 (2162/3145) in the validation cohort. These findings provide new insights into the pathogenic mechanisms of LOAD.

RNA-Sequencing Analysis Identification of Potential Biomarkers for Diagnosis of Sarcopenia.

Sarcopenia is a geriatric disease associated with increased mortality and disability. Early diagnosis and intervention are required to prevent it. This study investigated biomarkers for sarcopenia by using a combination of comprehensive clinical data and messenger RNA-sequencing (RNA-seq) analysis obtained from peripheral blood mononuclear cells. We enrolled a total of 114 older adults aged 66-94 years (52 sarcopenia diagnosed according to the Asian Working Group for Sarcopenia 2019 consensus and 62 normal older people). We used clinical data which were not included diagnosis criteria of sarcopenia, and stride length showed significance by logistic regression analysis (Bonferroni corrected p = .012, odds ratio = 0.14, 95% confidence interval [CI]: 0.05-0.40). RNA-seq analysis detected 6 differential expressed genes (FAR1, GNL2, HERC5, MRPL47, NUBP2, and S100A11). We also performed gene-set enrichment analysis and detected 2 functional modules (ie, hub genes, MYH9, and FLNA). By using any combination of the 9 candidates and basic information (age and sex), risk-prediction models were constructed. The best model by using a combination of stride length, HERC5, S100A11, and FLNA, achieved a high area under the curve (AUC) of 0.91 in a validation cohort (95% CI: 0.78-0.95). The quantitative PCR results of the 3 genes were consistent with the trend observed in the RNA-seq results. When BMI was added, the model achieved a high AUC of 0.95 (95% CI: 0.84-0.99). We have discovered potential biomarkers for the diagnosis of sarcopenia. Further refinement may lead to their future practical use in clinical use.

Cross-ancestry genome-wide analysis of atrial fibrillation unveils disease biology and enables cardioembolic risk prediction.

Atrial fibrillation (AF) is a common cardiac arrhythmia resulting in increased risk of stroke. Despite highly heritable etiology, our understanding of the genetic architecture of AF remains incomplete. Here we performed a genome-wide association study in the Japanese population comprising 9,826 cases among 150,272 individuals and identified East Asian-specific rare variants associated with AF. A cross-ancestry meta-analysis of >1 million individuals, including 77,690 cases, identified 35 new susceptibility loci. Transcriptome-wide association analysis identified IL6R as a putative causal gene, suggesting the involvement of immune responses. Integrative analysis with ChIP-seq data and functional assessment using human induced pluripotent stem cell-derived cardiomyocytes demonstrated ERRg as having a key role in the transcriptional regulation of AF-associated genes. A polygenic risk score derived from the cross-ancestry meta-analysis predicted increased risks of cardiovascular and stroke mortalities and segregated individuals with cardioembolic stroke in undiagnosed AF patients. Our results provide new biological and clinical insights into AF genetics and suggest their potential for clinical applications.

Early-onset Alzheimer Disease Associated With Neuromyelitis Optica Spectrum Disorder.

Neuromyelitis optica spectrum disorder (NMOSD) is an autoimmune demyelinating disease of the central nervous system. Although recent reports have noted that cognitive impairment is common in NMOSD, little longitudinal information is available on the trajectories of cognitive function in the disease. Here, we report a case of a 55-year-old woman with an 11-year history of NMOSD who visited our memory clinic for progressive memory loss. She was diagnosed with early-onset Alzheimer disease based on amyloid and tau positron emission tomography imaging biomarkers. This is the first report of early-onset Alzheimer disease in a patient with NMOSD. Complications of Alzheimer disease should be considered when patients with NMOSD exhibit rapid cognitive decline. More longitudinal studies of NMOSD with cognitive impairment are needed.

Deep learning-based age estimation from chest X-rays indicates cardiovascular prognosis.

BACKGROUND: In recent years, there has been considerable research on the use of artificial intelligence to estimate age and disease status from medical images. However, age estimation from chest X-ray (CXR) images has not been well studied and the clinical significance of estimated age has not been fully determined. METHODS: To address this, we trained a deep neural network (DNN) model using more than 100,000 CXRs to estimate the patients' age solely from CXRs. We applied our DNN to CXRs of 1562 consecutive hospitalized heart failure patients, and 3586 patients admitted to the intensive care unit with cardiovascular disease. RESULTS: The DNN's estimated age (X-ray age) showed a strong significant correlation with chronological age on the hold-out test data and independent test data. Elevated X-ray age is associated with worse clinical outcomes (heart failure readmission and all-cause death) for heart failure. Additionally, elevated X-ray age was associated with a worse prognosis in 3586 patients admitted to the intensive care unit with cardiovascular disease. CONCLUSIONS: Our results suggest that X-ray age can serve as a useful indicator of cardiovascular abnormalities, which will help clinicians to predict, prevent and manage cardiovascular diseases.

Chest X-ray is one of the most widely used medical imaging tests worldwide to diagnose and manage heart and lung diseases. In this study, we developed a computer-based tool to predict patients' age from chest X-rays. The tool precisely estimated patients' age from chest X-rays. Furthermore, in patients with heart failure and those admitted to the intensive care unit for cardiovascular disease, elevated X-ray age estimated by our tool was associated with poor clinical outcomes, including readmission for heart failure or death from any cause. With further testing, our tool may help clinicians to predict outcomes in patients with heart disease based on a simple chest X-ray.

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.

Network-based meta-analysis and the candidate gene association studies reveal novel ethnicity-specific variants in MFSD3 and MRPL43 associated with dementia with Lewy bodies.

Dementia with Lewy bodies (DLB) is the second most common form of neurodegenerative dementia in elderly people, following Alzheimer's disease. Only three genes, SNCA (α-synuclein), APOE (apolipoprotein E), and GBA (glucosylceramidase), have been convincingly demonstrated to be associated with DLB. Here, we applied whole-genome sequencing to blood samples from 61 DLB patients and 45 cognitively normal controls. We used accumulation of candidate mutations to detect novel DLB-associated genes. Subsequent single nucleotide polymorphism (SNP) genotyping and association studies in a large number of samples from Japanese individuals revealed novel heterozygous variants in MFSD3 (rs143475431, c.888T>A:p.C296*; n = 5,421, p = 0.00063) and MRPL43 (chr10:102746730, c.241A>C:p.N81H; n = 4,782, p = 0.0029). We further found that the MFSD3 variant increased plasma levels of butyrylcholinesterase (n = 1,206, p = 0.029). We believe that our findings will contribute to the understanding of DLB and provide insight into its pathogenic mechanism for future studies.

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

Alzheimer's disease (AD) is the most common multifactorial neurodegenerative disease among elderly people. Genome-wide association studies (GWAS) have been highly successful in identifying genetic risk factors. However, GWAS investigate common variants, which tend to have small effect sizes, and rare variants with potentially larger phenotypic effects have not been sufficiently investigated. Whole-genome sequencing (WGS) enables us to detect those rare variants. Here, we performed rare-variant association studies by using WGS data from 140 individuals with probable AD and 798 cognitively normal elder controls (CN), as well as single-nucleotide polymorphism genotyping data from an independent large Japanese AD cohort of 1604 AD and 1235 CN subjects. We identified two rare variants as candidates for AD association: a missense variant in OR51G1 (rs146006146, c.815 G > A, p.R272H) and a stop-gain variant in MLKL (rs763812068, c.142 C > T, p.Q48X). Subsequent in vitro functional analysis revealed that the MLKL stop-gain variant can contribute to increases not only in abnormal cells that should die by programmed cell death but do not, but also in the ratio of Aß42 to Aß40. We further detected AD candidate genes through gene-based association tests of rare variants; a network-based meta-analysis using these candidates identified four functionally important hub genes (NCOR2, PLEC, DMD, and NEDD4). Our findings will contribute to the understanding of AD and provide novel insights into its pathogenic mechanisms that can be used in future studies.