A longer time to relapse is associated with a larger increase in differences between paired primary and recurrent IDH wild-type glioblastomas at both the transcriptomic and genomic levels.

Glioblastoma (GBM) is the most common malignant brain tumor in adults, which remains incurable and often recurs rapidly after initial therapy. While large efforts have been dedicated to uncover genomic/transcriptomic alternations associated with the recurrence of GBMs, the evolutionary trajectories of matched pairs of primary and recurrent (P-R) GBMs remain largely elusive. It remains challenging to identify genes associated with time to relapse (TTR) and construct a stable and effective prognostic model for predicting TTR of primary GBM patients. By integrating RNA-sequencing and genomic data from multiple datasets of patient-matched longitudinal GBMs of isocitrate dehydrogenase wild-type (IDH-wt), here we examined the associations of TTR with heterogeneities between paired P-R GBMs in gene expression profiles, tumor mutation burden (TMB), and microenvironment. Our results revealed a positive correlation between TTR and transcriptomic/genomic differences between paired P-R GBMs, higher percentages of non-mesenchymal-to-mesenchymal transition and mesenchymal subtype for patients with a short TTR than for those with a long TTR, a high correlation between paired P-R GBMs in gene expression profiles and TMB, and a negative correlation between the fitting level of such a paired P-R GBM correlation and TTR. According to these observations, we identified 55 TTR-associated genes and thereby constructed a seven-gene (ZSCAN10, SIGLEC14, GHRHR, TBX15, TAS2R1, CDKL1, and CD101) prognostic model for predicting TTR of primary IDH-wt GBM patients using univariate/multivariate Cox regression analyses. The risk scores estimated by the model were significantly negatively correlated with TTR in the training set and two independent testing sets. The model also segregated IDH-wt GBM patients into two groups with significantly divergent progression-free survival outcomes and showed promising performance for predicting 1-, 2-, and 3-year progression-free survival rates in all training and testing sets. Our findings provide new insights into the molecular understanding of GBM progression at recurrence and potential targets for therapeutic treatments.

Classifying Alzheimer's disease and normal subjects using machine learning techniques and genetic-environmental features.

BACKGROUND: Alzheimer's disease (AD) is complicated by multiple environmental and polygenetic factors. The accuracy of artificial neural networks (ANNs) incorporating the common factors for identifying AD has not been evaluated. METHODS: A total of 184 probable AD patients and 3773 healthy individuals aged 65 and over were enrolled. AD-related genes (51 SNPs) and 8 environmental factors were selected as features for multilayer ANN modeling. Random Forest (RF) and Support Vector Machine with RBF kernel (SVM) were also employed for comparison. Model results were verified using traditional statistics. RESULTS: The ANN achieved high accuracy (0.98), sensitivity (0.95), and specificity (0.96) in the intrinsic test for AD classification. Excluding age and genetic data still yielded favorable results (accuracy: 0.97, sensitivity: 0.94, specificity: 0.96). The assigned weights to ANN features highlighted the importance of mental evaluation, years of education, and specific genetic variations (CASS4 rs7274581, PICALM rs3851179, and TOMM40 rs2075650) for AD classification. Receiver operating characteristic analysis revealed AUC values of 0.99 (intrinsic test), 0.60 (TWB-GWA), and 0.72 (CG-WGS), with slightly lower AUC values (0.96, 0.80, 0.52) when excluding age in ANN. The performance of the ANN model in AD classification was comparable to RF, SVM (linear kernel), and SVM (RBF kernel). CONCLUSIONS: The ANN model demonstrated good sensitivity, specificity, and accuracy in AD classification. The top-weighted SNPs for AD prediction were CASS4 rs7274581, PICALM rs3851179, and TOMM40 rs2075650. The ANN model performed similarly to RF and SVM, indicating its capability to handle the complexity of AD as a disease entity.

TOMM40 Genetic Variants Cause Neuroinflammation in Alzheimer's Disease.

Translocase of outer mitochondrial membrane 40 (TOMM40) is located in the outer membrane of mitochondria. TOMM40 is essential for protein import into mitochondria. TOMM40 genetic variants are believed to increase the risk of Alzheimer's disease (AD) in different populations. In this study, three exonic variants (rs772262361, rs157581, and rs11556505) and three intronic variants (rs157582, rs184017, and rs2075650) of the TOMM40 gene were identified from Taiwanese AD patients using next-generation sequencing. Associations between the three TOMM40 exonic variants and AD susceptibility were further evaluated in another AD cohort. Our results showed that rs157581 (c.339T > C, p.Phe113Leu, F113L) and rs11556505 (c.393C > T, p.Phe131Leu, F131L) were associated with an increased risk of AD. We further utilized cell models to examine the role of TOMM40 variation in mitochondrial dysfunction that causes microglial activation and neuroinflammation. When expressed in BV2 microglial cells, the AD-associated mutant (F113L) or (F131L) TOMM40 induced mitochondrial dysfunction and oxidative stress-induced activation of microglia and NLRP3 inflammasome. Pro-inflammatory TNF-α, IL-1ß, and IL-6 released by mutant (F113L) or (F131L) TOMM40-activated BV2 microglial cells caused cell death of hippocampal neurons. Taiwanese AD patients carrying TOMM40 missense (F113L) or (F131L) variants displayed an increased plasma level of inflammatory cytokines IL-6, IL-18, IL-33, and COX-2. Our results provide evidence that TOMM40 exonic variants, including rs157581 (F113L) and rs11556505 (F131L), increase the AD risk of the Taiwanese population. Further studies suggest that AD-associated mutant (F113L) or (F131L) TOMM40 cause the neurotoxicity of hippocampal neurons by inducing the activation of microglia and NLRP3 inflammasome and the release of pro-inflammatory cytokines.

Association of Polymorphisms of the Tissue Inhibitors of Metalloproteinases- 1 and -2 with Alzheimer's Disease in Taiwan.

BACKGROUND: Alzheimer's disease (AD) leads to progressive neuronal loss and cognitive and behavioral decline in the aging population. Matrix metalloproteinases (MMPs) and associated tissue inhibitors of metalloproteinases (TIMPs) are involved in remodeling the extracellular matrix. Amyloid beta-42 interrupts the integrity of the neurovascular unit and induces a toxic reaction affecting neurons. OBJECTIVE: This study investigated the relationships among genetic variants of the MMP-2, MMP-9, TIMP-1, and TIMP-2 genes and AD. METHODS: Two hundred and thirteen probable AD patients and 315 control participants of the Taiwan population were recruited for primary investigations, and we used the data of 763 participants from the Taiwan Biobank (TWB), as controls, for validation. Multivariable logistic regression was performed with adjustments for age, sex, hypertension, diabetes mellitus (DM), and alcohol consumption. The associations between the genotypes and allele frequencies and the SNP-associated AD hereditary models were analyzed using the SNPassoc package for R. We performed a permutation test with 1,000 replicates for the empirical estimates. RESULTS: A total of 213 probable AD patients and 315 control participants were recruited. The frequency of the A alleles in rs7503726 (G > A) in TIMP-2 was lower in the AD patients (p < 0.01). The frequencies of the TIMP-2 rs7503726 G/A and A/A genotypes were also significantly lower in the AD patients (p = 0.02) than in the controls and TWB. The TIMP-2 rs7503726 AA genotype was associated with a protective effect of AD in additive and recessive hereditary models (OR = 0.54, 95% CI: 0.32 - 0.92, p = 0.02; OR = 0.68, 95% CI: 0.50 - 0.92, p = 0.01, respectively). CONCLUSION: The TIMP-2 rs7503726 AA genotype was inversely correlated with AD susceptibility, and the presence of minor alleles of rs7503726 (A allele) have protective effects against AD.

Association Study of Alcohol Dehydrogenase and Aldehyde Dehydrogenase Polymorphism With Alzheimer Disease in the Taiwanese Population.

Alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH) are two major alcohol-metabolizing enzymes. Moderate alcohol intake is a protective modified factor in Alzheimer's disease (AD) while heavy alcohol intake and abstinence increased dementia risk. The associations between Alzheimer's disease and alcohol-metabolizing genes are uncertain. This study examined the association of AD with seven ADH/ALDH single-nucleotide polymorphisms (SNPs), ADH1C rs2241894, ADH1B rs1229984, ALDH1B1 rs2073478, ALDH2 rs886205, rs4767944, rs4648328, and rs671. We enrolled 157 AD and 168 age- and sex-matched control subjects in pilot study to examine the association of AD with ADH/ALDH SNPs. Reconstructed ALDH2 haplotypes were performed. We measured plasma level of ADH1C and checked the interaction effect of AD-rs2241894 genotype on plasma ADH1C level. In extension study, we further examined 339 AD and 2,504 healthy control from the Taiwan Biobank. In pilot study, we observed that ADH1C rs2241894 TT genotype was negatively associated with AD in a recessive genetic model (OR = 0.25, 95% CI 0.09-0.75, p < 0.0001) in women. A strong linkage disequilibrium was observed among the four examined SNPs of ALDH2. No haplotype was related to AD. The plasma ADH1C level in AD was higher than that in control. After adjusted by age, sex, hypertension, diabetes mellitus, and alcohol, we found a significant interaction effect of AD-rs2241894 genotype on plasma ADH1C level (p = 0.04). This interaction effect was attributable to the association between AD and plasma ADH1C level (ß estimate = 366, 95% CI 92.7∼639.4, p = 0.009). The genetic distribution of ADH1C rs2241894 showed strong ethnic heterogeneity, in which the T allele was the minor allele accounting for 28.5% in our study and 23.6% in East Asians, while it was a major allele in Americans, Europeans, and the global populations. No association was discovered between AD and the five SNPs: rs2241894, rs1229984, rs2073478, rs886205, and rs671 in the extension study. In summary, this study revealed a suggestive association between ADH1C rs2241894 and female AD in the pilot study, but failed to confirm this finding in a population database. Further age-matched and large sample size case-control studies are needed before rs2241894 can be interpreted as a protective genetic factor of AD.

Genetic Variants behind Cardiovascular Diseases and Dementia.

Cardiovascular diseases (CVDs) and dementia are the leading causes of disability and mortality. Genetic connections between cardiovascular risk factors and dementia have not been elucidated. We conducted a scoping review and pathway analysis to reveal the genetic associations underlying both CVDs and dementia. In the PubMed database, literature was searched using keywords associated with diabetes mellitus, hypertension, dyslipidemia, white matter hyperintensities, cerebral microbleeds, and covert infarctions. Gene lists were extracted from these publications to identify shared genes and pathways for each group. This included high penetrance genes and single nucleotide polymorphisms (SNPs) identified through genome wide association studies. Most risk SNPs to both diabetes and dementia participate in the phospholipase C enzyme system and the downstream nositol 1,4,5-trisphosphate and diacylglycerol activities. Interestingly, AP-2 (TFAP2) transcription factor family and metabolism of vitamins and cofactors were associated with genetic variants that were shared by white matter hyperintensities and dementia, and by microbleeds and dementia. Variants shared by covert infarctions and dementia were related to VEGF ligand-receptor interactions and anti-inflammatory cytokine pathways. Our review sheds light on future investigations into the causative relationships behind CVDs and dementia, and can be a paradigm of the identification of dementia treatments.

Memory Complaint Is a Surrogate for Memory Decline in the Middle-Aged: A Register-Based Study.

Memory complaint is one of the earliest symptoms of dementia. The causes and prognosis of memory complaint in the middle-aged population remain largely unknown. We reviewed the register-based data of 2129 patients with memory complaints. Among them, 404 participants were between 40 and 65 years old. The participants were separated into three groups: subjective cognitive decline (SCD), neurodegenerative diseases (ND), and non-neurodegenerative diseases (NND). One-year decline was defined as a decrease of ≥1 on the mini-mental state examination (MMSE). At baseline, 131 participants (32%) were diagnosed with SCD, 141 (35%) with ND, and 132 (33%) with NND. The 1-year cognitive decline rate was higher among patients with ND (36.8%) than in the SCD (7.3%, p = 1.3 × 10-8) and NND groups (7.6%, p = 1.1 × 10-7). One-year decline did not differ between the SCD and NND groups. Lower baseline MMSE score predicted increased risk of 1-year cognitive decline (odds ratio (OR) = 1.126, 95% confidence interval (CI) = 1.076-1.178, p = 2.52 × 10-7). Memory complaint in middle age carried a risk of 1-year cognitive decline, and baseline MMSE is an independent predictor of decline. An initial diagnosis of SCD held the same risk effect for decline as NND. These findings highlighted the necessity for neuropsychological tests in those with memory complaints presenting to the clinic.

Prediction of in-hospital stroke mortality in critical care unit.

BACKGROUND: Critical stroke causes high morbidity and mortality. We examined if variables in the early stage of critical stroke could predict in-hospital mortality. METHODS: We recruited 611 ischemic and 805 hemorrhagic stroke patients who were admitted within 24 h after the symptom onset. Data were analyzed with independent t test and Chi square test, and then with multivariate logistic regression analysis. RESULTS: In ischemic stroke, National Institutes of Health Stroke Scale (NIHSS) score (OR 1.08; 95 % CI 1.06-1.11; P < 0.01), white blood cell count (OR 1.11; 95 % CI 1.05-1.18; P < 0.01), systolic blood pressure (BP) (OR 0.49; 95 % CI 0.26-0.90; P = 0.02) and age (OR 1.03; 95 % CI 1.00-1.05; P = 0.03) were associated with in-hospital mortality. In hemorrhagic stroke, NIHSS score (OR 1.12; 95 % CI 1.09-1.14; P < 0.01), systolic BP (OR 0.25; 95 % CI 0.15-0.41; P < 0.01), heart disease (OR 1.94; 95 % CI 1.11-3.39; P = 0.02) and creatinine (OR 1.16; 95 % CI 1.01-1.34; P = 0.04) were related to in-hospital mortality. Nomograms using these significant predictors were constructed for easy and quick evaluation of in-hospital mortality. CONCLUSION: Variables in acute stroke can predict in-hospital mortality and help decision-making in clinical practice using nomogram.

Polymorphisms in the Promoters of the MMP-2 and TIMP-2 Genes Are Associated with Spontaneous Deep Intracerebral Hemorrhage in the Taiwan Population.

BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is a devastating stroke subtype. Matrix metalloproteinases (MMPs) function in the degradation of extracellular matrix and the activities of MMPs are modulated by their endogenous inhibitors, tissue inhibitors of metalloproteinases (TIMPs). This study aimed to discuss relationship of MMP-2 and TIMP-2 to spontaneous deep ICH (SDICH) susceptibility and hematoma size. METHODS: Associations were tested by logistic regression and general linear models (GLM) where appropriate, adjusting with covariables of age, sex, hypertension, diabetes mellitus, smoking, and alcohol consumption. Association analyses were performed first by stratification of genders and then by the age of 65 years old (y/o). Elder population was defined as subjects who were older than 65 y/o. RESULTS: There were 396 SDICH patients and 376 control subjects in this study. In the elder group, rs7503607 C>A variant in TIMP-2 was associated with SDICH in male and overall patients (OR = 3.49, 95% CI 1.45 to 8.40, P = 0.005 and OR = 2.45, 95% CI 1.37 to 4.38, P = 0.003, respectively) in additive genetic model. In recessive genetic model, rs2285053 TT genotype in MMP-2 was correlated to SDICH in male patients and overall elder group (OR = 7.30, 95% CI 1.3 to 40, P = 0.02 and OR = 2.91, 95% CI 1.02 to 8.31, P = 0.046, respectively), and rs7503726 AA genotype in TIMP-2 was associated with SDICH in female patients (OR = 0.29, 95% CI 0.1 to 0.84, P = 0.02). In younger male and overall younger patients, SDICH patients who had supratentorial hemorrhage had significantly lower frequency of AA genotypes in rs7503726 than those with infratentorial hemorrhage (OR = 0.36, 95% CI 0.17 to 0.75, P = 0.006 and OR = 0.43, 95% CI 0.22 to 0.84, P = 0.014, respectively). Hemorrhage size increased by 9.7 (95% CI 2.1 to 43, P = 0.004) cm3 per minor allele (A) of the rs7503607 variant in the elder female patients and increased by 4.3 (95% CI 1.4 to 12.9, P = 0.009) cm3 per minor allele (A) in all elder patients. In younger patients, the hemorrhage size decreased by 3.3 (95% CI 1.2 to 9.5, P = 0.03) cm3 per minor allele of the s7503726 variant in the female patients. CONCLUSIONS: This study showed a significant association between the variants of MMP-2 and TIMP-2 promoters and SDICH susceptibility with significant age and gender differences. Hemorrhage location and size might be affected by TIMP-2 promoter variants in the SDICH patients.

Association of MMP-9 Haplotypes and TIMP-1 Polymorphism with Spontaneous Deep Intracerebral Hemorrhage in the Taiwan Population.

BACKGROUND: Spontaneous deep intracerebral hemorrhage (SDICH) is a devastating stroke subtype. The causes of SDICH are heterogeneous. Matrix metalloproteinase-9 (MMP-9, Gelantinase B) has been shown to relate to stroke and the development of aneurysm and may increase risks of intracerebral hemorrhage. MMP activities are modulated by their endogenous inhibitors, tissue inhibitors of metalloproteinases (TIMPs). We analyzed the genetic variants of MMP-9 and TIMP-1 and SDICH susceptibility. METHODS: Associations were tested by logistic regression or general linear models with adjusting for multiple covariables. Multiplicative terms between genes were applied to detect the interaction effects on SDICH. Permutation testing of 1,000 replicates was performed for empirical estimates. RESULTS: In the group of ≥65 years old (y/o), we found associations of SDICH with rs3787268 (Odds ratio [OR] = 0.48, 95% confidence interval [CI] 0.27 to 0.86, P = 0.01) and haplotype1 (Hap1) (OR = 0.48, 95% CI 0.26 to 0.86, P = 0.014). For TIMP1 gene, rs4898 was associated with SDICH in the elder male group (OR = 0.35, 95% CI 0.15 to 0.81, P = 0.015). In contrast, in the younger male group, there were associations of SDICH with rs2250889 (OR = 0.48, 95% CI 0.27 to 0.84, P = 0.01) and Hap3 (OR = 0.61, 95% CI 0.38 to 0.97, P = 0.04). We found significant genetic interaction between TIMP-1 and MMP-9 in SDICH susceptibility among younger male subjects (P = 0.004). In subjects carrying rs4898 minor allele, carriers with Hap3 had lower SDICH risk than non-carriers (OR = 0.19, 95% CI 0.07 to 0.51, P = 0.001). In addition, this study showed that when young males were exposed to alcohol, Hap3 was a protective factor of SDICH (OR = 0.06, 95% CI 0.01 to 0.27, P = 0.0002). In contrast, when they were exposed to smoke, Hap2 carriers had increased risk of SDICH (OR = 2.45, 95% CI 1.05 to 5.73, P = 0.04). CONCLUSIONS: This study showed modest to moderate effects of MMP-9 and TIMP-1 polymorphisms on SDICH risks with significant age differences. MMP-9 may interact with alcohol to play a role in the SDICH risk in young men.