Search Results (146)

Apolipoprotein E (APOE) remains the most robust and widely replicated genetic risk factor for late-onset Alzheimer’s disease (AD) susceptibility, with the ε4 allele (APOE4) demonstrating profound associations with accelerated symptom manifestation, enhanced disease trajectory, and modified therapeutic responsiveness. This comprehensive review synthesizes contemporary evidence regarding the clinical utility of APOE4 genotyping, emphasizing its integration into personalized therapeutic frameworks and early diagnostic paradigms. The APOE4 variant exerts pathogenic influence through impaired amyloid-β clearance, enhanced tau pathology, and compromised neuronal repair mechanisms that alter disease phenotype. We systematically examine available genotyping methodologies, encompassing polymerase chain reaction (PCR) and next-generation sequencing (NGS) platforms, and evaluate their practical implementation within clinical environments. Recent investigations demonstrate that APOE4 status profoundly influences therapeutic efficacy, particularly with anti-amyloid interventions such as lecanemab, where carriers exhibit enhanced treatment response alongside increased adverse event susceptibility. Emerging gene therapeutic approaches show promise in mitigating APOE4-associated risks through targeted molecular interventions. The integration of APOE4 genotyping with fluid biomarkers and neuroimaging techniques enables refined patient stratification and enhanced diagnostic precision, facilitating earlier intervention windows that optimize therapeutic outcomes before irreversible neuronal damage occurs. This review underscores APOE4 testing as a transformative component of precision medicine in AD management, emphasizing its contribution to diagnostic refinement, clinical decision support, and targeted therapeutic interventions. Full article

While most of the Alzheimer’s disease (AD) cases are sporadic and manifest after age 65 (late-onset AD, LOAD), a subset of patients develop symptoms earlier in life (early-onset, EOAD) due to mutations in the PSEN1, PSEN2, or APP genes with an autosomal-dominant inheritance pattern (AD-EOAD). In this study, we examined the association between age of onset (AoO) and first clinical manifestation (FCM) with the APOE and DAOA genotypes, previously described as modifiers of clinical phenotypes in LOAD and EOAD in 88 individuals clinically diagnosed with AD-EOAD due to the PSEN1 A431E variant (39 females, 49 males). We classified the population according to their genotype (APOEε2, APOEε3, and APOEε4 and DAOA G/G, G/A, and A/A) and FCM (cognitive, behavioral, motor, and memory impaired). Memory impairment was the most frequent symptom (51%), followed by motor disturbances (31.8%), cognitive symptoms other than memory (10.4%), and behavioral changes (6.8%). We found a significant association between APOE genotype and AoO (p < 0.001), with the APOEε4 allele being linked to a delayed onset (β = 4.04, SE = 1.11, p = 0.0003). Similarly, individuals with the DAOA rs2391191 A/A genotype showed a significantly later AoO compared to G/G carriers (β = 2.13, SE = 0.96, p = 0.0301). No significant association was found between APOE or DAOA genotypes and FCM. The findings suggest that both the APOEε4 allele and DAOA rs2391191 A/A genotype may act as genetic modifiers of AoO, delaying symptom onset in individuals with AD-EOAD. Further research is needed to elucidate the molecular pathways through which APOE and DAOA influence AD-EOAD progression. Full article

Alzheimer’s disease (AD) is a complex neurodegenerative condition which, despite its high prevalence and socioeconomic impact on the world, has an etiology that remains poorly understood. The genetic causes of AD are complex and have been continuously studied for decades. They range from rare pathogenic, highly penetrant mutations in early-onset (EOAD) forms, which account for 5% of the cases to multiple-risk alleles across different genes in late-onset (LOAD) forms. Monogenic causes of EOAD allocate within APP, PSEN1, and PSEN2 genes in 10–15% of cases. The most significant risk factor in LOAD heritability is the APOE ε4 allele, as well as numerous loci within genes involved in immunity, endocytosis, lipid metabolism, and amyloid and tau processing. LOAD can also be attributed to the accumulation of somatic mutations, which may be detected by analysis of brain-derived cell-free DNA (cfDNA) in plasma. This review offers a comprehensive overview of the genetic architecture of Alzheimer’s disease, with particular focus on the molecular mechanisms underlying both early- and late-onset forms of the condition. An improved understanding of the genetic etiology of AD can aid better prevention, earlier diagnosis, and novel therapeutic approaches. This can be achieved by analyzing understudied populations, performing case-control studies with appropriately matched controls, and surveying brain-derived cell-free DNA in plasma, with the latter having the potential to contribute to the implementation of liquid biopsy in dementology. Full article

Background: The biological mediators for the epidemiologic overlap between osteoporosis and dementia are unclear. We undertook a scoping review of clinical studies to identify genetic and biological factors linked with these degenerative conditions, exploring the mechanisms and pathways connecting both conditions. Methods: Studies selected (1) involved clinical research investigating genetic factors or biomarkers associated with dementia or osteoporosis, and (2) were published in English in a peer-reviewed journal between July 1993 and March 2025. We searched Medline Ovid, Embase, PsycINFO, the Cochrane Library, the Web of Science databases, Google Scholar, and the reference lists of studies following the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR). Results: Twenty-three studies were included in this review. These explored the role of the APOE polymorphism (n = 2) and the APOE4 allele (n = 13), associations between TREM2 mutation and late onset AD (n = 1), and associations between amyloid beta and bone remodeling (n = 1); bone-related biomarkers like DKK1, OPG, and TRAIL as predictors of cognitive change (n = 2); extracellular vesicles as bone–brain communication pathways (1); and the role of dementia-related genes (n = 1), AD-related CSF biomarkers (n = 1), and parathyroid hormone (PTH) (n = 1) in osteoporosis–dementia pathophysiology. Conclusions: Bone-related biomarkers active in the Wnt/β-Catenin pathway (Dkk1 and sclerostin) and the RANKL/RANK/OPG pathway (OPG/TRAIL ratio) present consistent evidence of involvement in AD and osteoporosis development. Reports proposing APOE4 as a causal genetic link for both osteoporosis and AD in women are not corroborated by newer observational studies. The role of Aβ toxicity in osteoporosis development is unverified in a large clinical study. Full article

To assess the association between known (PlGF, sFlt-1, betaHCG, PAPPA) and novel (cell-free DNA, cfDNA, and total endothelial and platelet microvesicles, MVs) maternal blood biomarkers measured at the first trimester with the later development of preeclampsia (PE) and PE-related severe adverse events (SAE), we conducted a retrospective case–control study including women with an established diagnosis of preeclampsia (cases) and healthy pregnant women (controls). Biomarkers were measured from first-trimester blood samples stored in a hospital biobank. A total of 89 women, 54 women with PE and 35 controls were included. PlGF showed good performance for diagnosing overall preeclampsia (AUC: 0.71; 95% CI 0.59–0.82), early-onset preeclampsia (AUC 0.80; 95% CI 0.68–0.9) and fetal-neonatal SAEs (AUC: 0.73; 95% CI 0.63–0.84). Multivariate models including clinical variables, PlGF and other biomarkers showed good to very good discrimination for the development of PE, early-onset PE and fetal-neonatal SAEs (AUCs of 0.87, 0.89 and 0.79, respectively). Platelet-derived MVs were the best isolated biomarker for late-onset PE and, combined with systolic blood pressure, showed good discrimination (AUC: 0.81; 95% CI 0.71–0.92). For maternal SAEs, a model incorporating cfDNA and sFlt-1 provided excellent discrimination (AUC 0.92; 95% CI 0.82–1.00). Our findings suggest that multivariate models incorporating both clinical variables and first-trimester biomarkers may improve risk stratification for PE, especially for late-onset PE and for identifying women at risk of severe maternal or fetal complications. Notably, the inclusion of novel biomarkers such as cfDNA and MVs added value in clinical scenarios where the predictive performance of existing tools remains suboptimal. Full article

Apolipoprotein E (APOE) alleles play distinct roles in the pathogenesis of Alzheimer’s disease (AD), with APOEε4 being the strongest genetic risk factor for late-onset AD, while APOEε2 appears protective. Despite extensive research, the precise mechanisms by which APOE alleles contribute to AD pathology remain incompletely understood. Recent advances in multi-omics technologies and single-cell analyses have revealed that APOE alleles shape microglial phenotypes, thereby affecting amyloid clearance, inflammatory responses, tau pathology, and lipid metabolism. In this review, we provide a detailed overview of how APOE alleles differentially regulate microglial activation, inflammatory signaling, phagocytic activity, and lipid metabolism in the context of AD, with a particular focus on the APOEε4-mediated disruption of microglial homeostasis via pathways such as TREM2 signaling, NF-κB/NLRP3 activation, ACSL1 upregulation, and HIF-1α induction. These insights not only advance our understanding of APOE allele-specific contributions to AD pathology, but also highlight novel therapeutic strategies targeting the APOE–microglia axis. Full article

Newborn screening laboratories are increasingly adding lysosomal storage disorders (LSDs), such as Mucopolysaccharidosis I (MPS I) and Pompe disease, to their screening panels. Without newborn screening, LSDs are frequently diagnosed only after the onset of symptoms; late detection can lead to profound and irreversible organ damage and mortality. While screening of these disorders has accelerated over the past five years, there is little published information regarding the potential correlation of demographic variables (age at sample collection, birthweight, gestational age, gender, etc.) with lysosomal enzyme activity. The Missouri State Public Health Laboratory prospectively screened more than 475,000 newborns for MPS I, Pompe disease, Gaucher disease, and Fabry disease between 15 January 2013 and 15 May 2018. This report investigates trends between several demographic variables and activities of four lysosomal enzymes: α-L-iduronidase (IDUA), acid α-glucosidase (GAA), acid β-glucocerebrosidase (GBA), and acid α-galactosidase (GLA). This information provides a valuable resource to newborn screening laboratories for the implementation of screening for lysosomal storage disorders and the establishment of screening cutoffs. Full article

Sleep is essential for physical and mental health, playing a critical role in memory consolidation, behavioral stability, and the regulation of immune and metabolic functions. The incidence of sleep disorders, particularly sleep deprivation (SD), increases with age and is prevalent in neurodegenerative and psychiatric disorders such as Alzheimer’s disease (AD). Nearly 40% of AD patients experience significant chronic sleep impairments. The clinical distinction between late-life sleep disorders and AD is often challenging due to overlapping symptoms, including cognitive decline and behavioral impairments. Although the exact causal relationship between SD and AD remains complex and multifaceted, strong evidence suggests a bidirectional link, with AD patients frequently exhibiting disrupted sleep architecture, reduced slow-wave activity, and shorter total sleep duration. On a pathophysiological level, SD contributes to neuroinflammation, amyloid-β plaque deposition, and tau tangles, which are key features of AD. Current treatments, such as sedatives and antidepressants, often have limitations, including inconsistent efficacy, dependency risks, and poor long-term outcomes/recurrence, highlighting the need for safer and more effective alternatives. This review examines the interplay between SD and AD and proposes omega (n)-3 fatty acids (FAs) as a potential therapeutic intervention. Preclinical and clinical studies suggest that n-3 supplementation may improve sleep onset/quality, reduce neuroinflammation, support synaptic function, and decrease amyloid-β aggregation, thereby alleviating early AD-related neurological changes. Given their safety profile and neuroprotective effects, n-3 FAs represent a promising strategy for managing the comorbidity of sleep disorders in AD. Full article

Alzheimer’s disease (AD) is a leading cause of dementia and a growing public health concern worldwide. Despite decades of research, effective disease-modifying treatments remain elusive, partly due to limitations in current experimental models. The purpose of this review is to critically assess and compare existing murine and alternative models of AD to identify key strengths, limitations, and future directions for model development that can enhance translational relevance and therapeutic discovery. Traditional transgenic mouse models have advanced the understanding of amyloid-beta and tau pathologies, but often fail to capture the complexity of sporadic, late-onset AD. In response, alternative models—including zebrafish, Drosophila melanogaster, Caenorhabditis elegans, non-human primates, and human brain organoids—are gaining traction due to their complementary insights and diverse experimental advantages. This review also discusses innovations in genetic engineering, neuroimaging, computational modelling, and drug repurposing that are reshaping the landscape of AD research. By integrating these diverse approaches, the review advocates for a multi-model, multidisciplinary strategy to improve the predictive power, accelerate clinical translation, and inform personalised therapeutic interventions. Ethical considerations and equitable access to diagnostics and emerging treatments are also emphasised. Ultimately, this work aims to support the development of more accurate, effective, and human-relevant models to combat AD. Full article

Newborn screening (NBS) is leading to the diagnosis of a large number of children with late-onset Pompe disease (LOPD), yet many remain asymptomatic until later years. A high-protein, low-carbohydrate diet is recommended for adults with LOPD. Nutrition guidelines are not available for young children. Methods: 37 children with LOPD aged 1–6 years participated. Early diet history, feeding practices, and 24 h dietary intake were collected via questionnaire. Anthropometric measurements, blood creatine kinase (CK), blood urea nitrogen (BUN)/creatinine ratio, and urine glucose tetrasaccharide (Glc4) were collected at clinic visits. A subset of 19 children received a clinical feeding assessment (CFA). Results: All patients derived their nutrition orally. Breastfeeding was successfully initiated in 73% of infants. Body weight ranged between 3 and 99% and height ranged from 4 to 97%. A tendency to be overweight and obese was noted in older children with LOPD. A total of 24% of the children who had CFA were diagnosed with dysphagia that was typically mild in severity and rarely affected their ability to eat a normal diet. Limiting added sugar and processed foods was the most widely used dietary practice followed by encouraging protein. Protein intake was three–four times higher than the recommended dietary intake (RDA). A high BUN/creatinine ratio was observed in some children, which may indicate incompatibility with protein intake and need for individualizing the diet. Conclusions: The results of this study provide a framework for developing future nutrition guidelines for children with LOPD by performing an individualized assessment of dietary intake, growth, feeding/swallowing, and laboratory parameters. Full article

Background: Emerging evidence suggests a potential link between heavy metals and Alzheimer’s disease and related dementias (AD/ADRD). This study compiled epidemiological evidence from research published over the past 11 years on the impact of metals on AD/ADRD in women. Women have unique risk factors for late onset of AD/ADRD, in addition to genetic factors, apolipoprotein E allele (APOE4), and longer life expectancy. Furthermore, women are twice likely as men to experience depression, which increases their risk of developing AD/ADRD. Our narrative review underscored the necessity of a sex-specific approach to address women’s vulnerability to AD/ADRD. Methods: Electronic databases, including PubMed, Google Scholar, NIOSH Toxline, and Scopus, were thoroughly searched to identify primary epidemiological studies on older women exposed to metals and published between 2014 to 2024. Results: We identified 34 epidemiological studies that met the inclusion criteria. The findings revealed a complex interplay between environmental metals such as lead (Pb), cadmium (Cd), arsenic (As), manganese (Mn), selenium (Se), iron (Fe), zinc (Zn), copper (Cu), magnesium (Mg), and calcium (Ca) and the risk of AD/ADRD in women. Significant adverse effects were reported for Cu, Cd, As, Pb, and Mn while significant protective effects were found between Se, Fe, and Zn in blood and AD/ADRD among older women. However, some studies also reported no correlations. Conclusions: Overall, our review identified contrasting results regarding the effects of metals on AD/ADRD in women. Future studies should collect additional evidence to understanding the effects of heavy metals on AD/ADRD in women for developing preventive measures. Full article

Lipid metabolism disorders represent a significant risk factor for the pathogenesis of Alzheimer’s disease (AD). Apolipoprotein E (APOE) has been regarded as a pivotal regulator of lipid homeostasis in the central nervous system (CNS), with polymorphic alleles identified as genetic risk factors for late-onset AD. Despite advances in APOE research and the development of numerous pharmaceutical approaches targeting distinct APOE isoforms, there remain limited treatment approaches for AD that focus on lipid metabolic homeostasis. Consequently, it is necessary to reevaluate the lipid metabolic process in the CNS. Apolipoprotein A1 (APOA-I), a major component of high-density lipoprotein (HDL), plays a crucial role in reverse cholesterol transport from tissues to the liver to maintain lipid homeostasis. Over the past few decades, numerous studies have suggested a connection between reduced APOA-I levels and a higher risk of AD. APOA-I is synthesized exclusively in the liver and intestines, and there is a lack of conclusive evidence supporting its functional significance within the central nervous system, in contrast to APOE, which is produced locally by glial cells and neurons within the CNS. Moreover, APOA-I’s ability to penetrate the blood-brain barrier (BBB) is still poorly understood, which causes its significance in central lipid metabolism and AD pathophysiology to be mainly disregarded. Recent advancements in tracing methodologies have underscored the essential role of APOA-I in regulating lipid metabolism in the CNS. This review aims to elucidate the physiological functions and metabolic pathways of APOA-I, integrating its associations with AD-related pathologies, risk factors, and potential therapeutic targets. Through this discourse, we aim to provide novel insights into the intricate relationship between AD and APOA-I, paving the way for future research in this field. Full article

The majority of early-onset colorectal cancers (EOCRCs) are not substantiated by germline variants in the main CRC predisposition genes (the “DIGE” panel). To identify potentially novel EOCRC-specific predisposition genes, we analyzed 585 cancer pathway genes in an EOCRC patient cohort (n = 87, diagnosis ≤ 40 years, DIGE-), and compared their variant spectrum to the GnomAD cancer-free database. We identified high-impact variants (HVs) in 15 genes significantly over-represented in EOCRC. Among the 32 unrelated patients with a CRC family history (i.e., with a potentially dominant transmission pattern), 9 presented HVs in ten genes, four of which had a DNA repair function. We subsequently sequenced these 15 genes in a cohort of 82 late-onset CRCs (diagnosis ≥ 50 years, DIGE-) and found variants in 11 of these genes to be specific to EOCRC. We then screened these 11 genes in our patient database (n = 6482), which only contained 2% of EOCRCs (DIGE-), and identified two other EOCRC cases diagnosed after our cohort constitution, with HVs in RECQL4 and NUTM1. Altogether, we found that 37.5% and 18.75% of patients carrying heterozygous NUTM1 and RECQL4 HVs, respectively, in our database were diagnosed with EOCRC. Our work has identified a pattern of germline variants not previously associated with EOCRC. Full article

Background: Comorbidities such as hypertension and hypercholesterolemia are risk factors associated with Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD). The most significant genetic risk factor is the ε4 allele of the apolipoprotein E gene (APOE). The aim of this paper is to determine whether hypertension is the most significant but modifiable risk factor to delay AD onset. Method: A cohort of patients with MCI (N = 3052) is developed from the documented database (N = 43,999) within the National Alzheimer’s Coordinating Center (NACC) during the time period from June 2005 to May 2021. Cox proportional hazard models with propensity score weights on demographic information and comorbidities at baseline are applied to examine association of hypertension and hypercholesterolemia with AD onset among MCI patients. Associations are compared to APOE genotypes and AD onset. In addition, the association of hypertension with decline rates in Mini-Mental State Examination (MMSE) scores are reported. Results: After controlling for age, sex, race, APOEε4, and reported comorbidities, the results show that MCI patients who subsequently develop hypertension within 18 months after their first diagnosis of MCI have a significantly higher risk of AD onset (HR = 2.77, 95%CI (1.66, 4.65), p value < 0.0001), compared to MCI patients with no hypertension or a late occurrence of hypertension after 18 months. This significant association is validated through a Random Forest method, a machine learning approach with bootstrap simulations. In addition, patients with early hypertension have significantly higher MMSE score declining rates compared to those without hypertension (coefficient = 0.988, p = 0.0054.). Conclusions: Hypertension is the most significant risk factor comparable to the genetic risk factor APOEε4 allele. Our finding is unique, as we did not observe a similar outcome in those with early hypercholesterolemia. Thus, among all comorbidities, hypertension is the most significant risk factor similar to the genetic risk factor APOEε4 allele. Full article

Introduction: Alzheimer’s disease (AD), and more specifically late-onset Alzheimer’s disease (LOAD), represents a considerable challenge in terms of early and timely diagnosis and treatment. Early diagnosis is crucial to improve the efficacy of the therapies and patients’ quality of life. The current challenge is to accurately identify at-risk individuals before the manifestations of the first symptoms of AD. Methods and results: Here, we present an improved model for LOAD risk prediction, which applies the k-nearest neighbors (KNN) algorithm. We have achieved a sensitivity of 0.80 and an area under the curve (AUC) of 0.71, which represents a high performance especially when compared to an AUC of 0.66 reported previously in 2019 using a KNN model. Discussion: The application of a mathematical model that combines genetic and clinical covariates showed a good prediction of the AD/LOAD risk, with the higher weight being the polygenic genetic risk, APOE haplotype, and age. Compared to previous studies, our model integrates and correlates genetic prediction together with phenotypic information by fine-tuning the parameters of the model in order to achieve the best performance. This algorithm can be used in the general population and does not require the manifestation of any symptoms for its effective application. Thus, we present here an advanced model for risk prediction of LOAD. Full article