DNA methylation is a critical epigenetic mechanism involved in numerous physiological processes. Alterations in DNA methylation patterns are associated with various brain disorders, including dementias such as Alzheimer’s disease (AD) and frontotemporal dementia (FTD). Investigating these alterations is essential for understanding the pathogenesis and progression of these disorders. Among the various methods for detecting DNA methylation, DNA sequencing is one of the most widely employed. Specifically, two main sequencing approaches are commonly used for DNA methylation analysis: bisulfite sequencing and single-molecule long-read sequencing. In this review, we compared the performances of CpG methylation detection obtained using two popular sequencing platforms, Illumina for bisulfite sequencing and Oxford Nanopore (ON) for long-read sequencing. Our comparison considers several factors, including accuracy, efficiency, genomic regions, costs, wet-lab protocols, and bioinformatics pipelines. We provide insights into the strengths and limitations of both methods with a particular focus on their application in research on AD and FTD.

Alzheimer’s disease (AD) and Frontotemporal lobar degeneration (FTLD) represent the most common forms of neurodegenerative dementias with a highly phenotypic variability. Herein, we investigated the role of genetic variants related to the immune system and inflammation as genetic modulators in AD and related dementias. In patients with sporadic AD/FTLD (n = 300) and GRN/C9orf72 mutation carriers (n = 80), we performed a targeted sequencing of 50 genes belonging to the immune system and inflammation, selected based on their high expression in brain regions and low tolerance to genetic variation. The linear regression analyses revealed two genetic variants: (i) the rs1049296 in the transferrin (TF) gene, shown to be significantly associated with age at onset in the sporadic AD group, anticipating the disease onset of 4 years for each SNP allele with respect to the wild-type allele, and (ii) the rs7550295 in the calsyntenin-1 (CLSTN1) gene, which was significantly associated with age at onset in the C9orf72 group, delaying the disease onset of 17 years in patients carrying the SNP allele. In conclusion, our data support the role of genetic variants in iron metabolism (TF) and in the modulation of the calcium signalling/axonal anterograde transport of vesicles (CLSTN1) as genetic modulators in AD and FTLD due to C9orf72 expansions.

Genetic frontotemporal lobar degeneration (FTLD) is characterized by heterogeneous phenotypic expression, with a disease onset highly variable even in patients carrying the same mutation. Herein we investigated if variants in lysosomal genes modulate the age of onset both in FTLD due to GRN null mutations and C9orf72 expansion. In a total of 127 subjects (n = 74 GRN mutations and n = 53 C9orf72 expansion carriers), we performed targeted sequencing of the top 98 genes belonging to the lysosomal pathway, selected based on their high expression in multiple brain regions. We described an earlier disease onset in GRN/C9orf72 pedigrees in subjects carrying the p.Asn521Thr variant (rs1043424) in PTEN-induced kinase 1 (PINK1), a gene that is already known to be involved in neurodegenerative diseases. We found that: (i) the PINK1 rs1043424 C allele is significantly associated with the age of onset; (ii) every risk C allele increases hazard by 2.11%; (iii) the estimated median age of onset in homozygous risk allele carriers is 10–12 years earlier than heterozygous/wild type homozygous subjects. A replication study in GRN/C9orf72 negative FTLD patients confirmed that the rs1043424 C allele was associated with earlier disease onset (−5.5 years in CC versus A carriers). Understanding the potential mechanisms behind the observed modulating effect of the PINK1 gene in FTLD might prove critical for identifying biomarkers and/or designing drugs to modify the age of onset, especially in GRN/C9orf72-driven disease.

Monogenic forms of Alzheimer’s Disease (AD) and Frontotemporal Dementia (FTD) represent the two principal neurodegenerative disorders leading to early-onset dementia, primarily linked to mutations in key AD- and FTD-associated genes. The marked heterogeneity in age at onset and penetrance among carriers of pathogenic mutations suggests that monogenic variants act within a broader polygenic background. The combined impact of AD- and FTD-related genetic variation on disease incidence in monogenic forms remains largely unexplored. Herein, we investigate gene–gene interaction patterns in monogenic AD and FTD, with a focus on genetic variability in key AD (APP, PSEN1, PSEN2) and FTD (MAPT, GRN, C9orf72)-associated genes and their association with cumulative disease incidence. Within the GARDENIA Consortium, we studied 426 individuals from Italian pedigrees, including patients (n = 319) and presymptomatic (n = 107) carriers of causative variants in APP (n = 39), PSEN1 (n = 71), PSEN2 (n = 13), MAPT (n = 29), GRN (n = 188), and C9orf72 (n = 86). Age at symptoms onset, age at last follow-up and sex were recorded. Whole exome sequencing was performed, focusing on non-causative variants (n = 64) in the key AD (APP, PSEN1, PSEN2) and FTD genes (MAPT, GRN, C9orf72). Weighted genetic burden scores were derived using Fine–Gray competing risk models to estimate variant-specific effects on cumulative AD and FTD incidence, accounting for mutually exclusive outcomes and family clustering. Model fit was evaluated using Akaike Information Criterion. Higher AD-risk-weighted burden scores in AD-related genes were associated with a significantly increased cumulative incidence of AD, while higher FTD-risk-weighted scores in FTD-related genes showed a trend toward association with increased cumulative incidence of FTD. A significant interaction between burden scores was observed. AD and FTD burden scores showed a negative interaction for AD (~79% attenuation) but a modest synergistic effect for FTD (~6% increase). These findings could imply context-dependent pleiotropy rather than simple additive genetic effects. Our study suggests that even in carriers oh highly penetrant AD or FTD causative variants, genetic background could substantially modulate cumulative disease incidence. Integrating polygenic information with monogenic status may improve prognostic stratification and inform precision approaches in dementia research and clinical trials.