Longitudinal cognitive decline in autosomal-dominant Alzheimer's disease varies with mutations in APP and PSEN1 genes

Critical thinking of Alzheimer's transgenic mouse model: current research and future perspective

Transgenic models are useful tools for studying the pathogenesis of and drug development for Alzheimer's Disease (AD). AD models are constructed usually using overexpression or knock-in of multiple pathogenic gene mutations from familial AD. Each transgenic model has its unique behavioral and pathological features. This review summarizes the research progress of transgenic mouse models, and their progress in the unique mechanism of amyloid-β oligomers, including the first transgenic mouse model built in China based on a single gene mutation (PSEN1 V97L) found in Chinese familial AD. We further summarized the preclinical findings of drugs using the models, and their future application in exploring the upstream mechanisms and multitarget drug development in AD.

A biomarker-validated time scale in years of disease progression has identified early- and late-onset subgroups in sporadic Alzheimer's disease

BACKGROUND

It is possible to calculate the number of years to the expected clinical onset (YECO) of autosomal-dominant Alzheimer's disease (adAD). A similar time scale is lacking for sporadic Alzheimer's disease (sAD). The purpose was to design and validate a time scale in YECO for patients with sAD in relation to CSF and PET biomarkers.

METHODS

Patients diagnosed with Alzheimer's disease (AD, n = 48) or mild cognitive impairment (MCI, n = 46) participated in the study. They underwent a standardized clinical examination at the Memory clinic, Karolinska University Hospital, Stockholm, Sweden, which included present and previous medical history, laboratory screening, cognitive assessment, CSF biomarkers (Aβ₄₂, total-tau, and p-tau), and an MRI of the brain. They were also assessed with two PET tracers, ¹¹C-Pittsburgh compound B and ¹⁸F-fluorodeoxyglucose. Assuming concordance of cognitive decline in sAD and adAD, YECO for these patients was calculated using equations for the relationship between cognitive performance, YECO, and years of education in adAD (Almkvist et al. J Int Neuropsychol Soc 23:195-203, 2017).

RESULTS

The mean current point of disease progression was 3.2 years after the estimated clinical onset in patients with sAD and 3.4 years prior to the estimated clinical onset in patients with MCI, as indicated by the median YECO from five cognitive tests. The associations between YECO and biomarkers were significant, while those between chronological age and biomarkers were nonsignificant. The estimated disease onset (chronological age minus YECO) followed a bimodal distribution with frequency maxima before (early-onset) and after (late-onset) 65 years of age. The early- and late-onset subgroups differed significantly in biomarkers and cognition, but after control for YECO, this difference disappeared for all except the APOE e4 gene (more frequent in early- than in late-onset).

CONCLUSIONS

A novel time scale in years of disease progression based on cognition was designed and validated in patients with AD using CSF and PET biomarkers. Two early- and late-disease onset subgroups were identified differing with respect to APOE e4.

Shared and unique effects of ApoEε4 and pathogenic gene mutation on cognition and imaging in preclinical familial Alzheimer's disease

BACKGROUND

Neuropsychology and imaging changes have been reported in the preclinical stage of familial Alzheimer's disease (FAD). This study investigated the effects of APOEε4 and known pathogenic gene mutation on different cognitive domains and circuit imaging markers in preclinical FAD.

METHODS

One hundred thirty-nine asymptomatic subjects in FAD families, including 26 APOEε4 carriers, 17 APP and 20 PS1 mutation carriers, and 76 control subjects, went through a series of neuropsychological tests and MRI scanning. Test scores and imaging measures including volumes, diffusion indices, and functional connectivity (FC) of frontostriatal and hippocampus to posterior cingulate cortex pathways were compared between groups and analyzed for correlation.

RESULTS

Compared with controls, the APOEε4 group showed increased hippocampal volume and decreased FC of fronto-caudate pathway. The APP group showed increased recall scores in auditory verbal learning test, decreased fiber number, and increased radial diffusivity and FC of frontostriatal pathway. All three genetic groups showed decreased fractional anisotropy of hippocampus to posterior cingulate cortex pathway. These neuropsychological and imaging measures were able to discriminate genetic groups from controls, with areas under the curve from 0.733 to 0.837. Circuit imaging measures are differentially associated with scores in various cognitive scales in control and genetic groups.

CONCLUSIONS

There are neuropsychological and imaging changes in the preclinical stage of FAD, some of which are shared by APOEε4 and known pathogenic gene mutation, while some are unique to different genetic groups. These findings are helpful for the early identification of Alzheimer's disease and for developing generalized and individualized prevention and intervention strategies.

APOE ε4 influences cognitive decline positively in APP and negatively in PSEN1 mutation carriers with autosomal-dominant Alzheimer's disease

BACKGROUND AND PURPOSE

The aim was to investigate the effect of APOE ε4 allele on cognitive decline in adAD. Presence of the APOE ε4 allele reduces age of symptom onset, increases disease progression, and lowers cognitive performance in sporadic Alzheimer's disease (AD), while the impact of the APOE ε4 allele in autosomal-dominant AD (adAD) is incompletely known.

METHODS

Mutation carriers (MCs; n = 39) and non-carriers (NCs; n = 40) from six adAD families harbouring a mutation in the APP (28 MCs and 25 NCs) or the PSEN1 genes (11 MCs and 15 NCs) underwent repeated cognitive assessments. A timeline of disease course was defined as years to expected age of clinical onset (YECO) based on history of disease onset in each family. The MC and NC groups were comparable with regard to demographics and prevalence of the APOE ε4 allele. The relationship between cognitive decline and YECO, YECO2 , education, APOE, and APOE-by-YECO interaction was analysed using linear mixed-effects models.

RESULTS

The trajectory of cognitive decline was significantly predicted by linear and quadratic YECO and education in MCs and was determined by age and education in NCs. Adding APOE ε4 allele (presence/absence) as a predictor did not change the results in the MC and NC groups. The outcome also remained the same for MCs and NCs after adding the APOE-by-YECO interaction as a predictor. Analyses of APP and PSEN1 MCs separately showed favourable APOE-by-YECO interaction in APP (less steep decline) and unfavourable interaction in PSEN1 (steeper decline), linked to the APOE ε4 allele.

CONCLUSION

The APOE ε4 allele influences cognitive decline positively in APP and negatively in PSEN1 mutation carriers with adAD, indicating a possible antagonistic pleiotropy.

A Young Man with Cognitive Impairment and a Heart Condition

A 43-year-old came to our observation for progressive cognitive impairment, confirmed by the neuropsychological evaluation. A diagnosis of multidomain amnestic mild cognitive impairment, due to unknown reasons, was posited at the first assessment. The patient’s neurological exam was otherwise completely normal. The patient’s mother was clinically diagnosed with frontotemporal dementia in her forties. The patient underwent neuroimaging investigations and cerebrospinal fluid analysis. Our diagnostic work-up pointed toward a neurodegenerative etiology, but the presence of concurrent cardiomyopathy emerged in the meantime. Due to the patient’s family history, a thorough genetic screening was performed. The results revealed a unique genetic asset, with heterozygotic variants of three amyloid-related genes (PSEN1, APP, and MYBPC3). PSEN1 and MYBPC3 mutations showed distinct pathogenic features and accounted for the patient’s brain and cardiac amyloidosis, whereas the APP variant was of uncertain pathological implications.

The APOE ε4 Allele Affects Cognitive Functions Differently in Carriers of APP Mutations Compared to Carriers of PSEN1 Mutations in Autosomal-Dominant Alzheimer's Disease

Mounting evidence shows that the APOE ε4 allele interferes with cognition in sporadic Alzheimer’s disease. Less is known about APOE in autosomal-dominant Alzheimer’s disease (adAD). The present study explored the effects on cognition associated with the gene–gene interactions between the APOE gene and the APP and PSEN1 genes in adAD. This study includes mutation carriers (MC) and non-carriers (NC) from adAD families with mutations in APP (n = 28 and n = 25; MC and NC, respectively) and PSEN1 (n = 12 and n = 15; MC and NC, respectively) that represent the complete spectrum of disease: AD dementia (n = 8) and mild cognitive impairment (MCI, n = 15 and presymptomatic AD, n = 17). NC represented unimpaired normal aging. There was no significant difference in the distribution of APOE ε4 (absence vs. presence) between the APP vs. PSEN1 adAD genes and mutation status (MC vs. NC). However, episodic memory was significantly affected by the interaction between APOE and the APP vs. PSEN1 genes in MC. This was explained by favorable performance in the absence of APOE ε4 in PSEN1 compared to APP MC. Similar trends were seen in other cognitive functions. No significant associations between APOE ε4 and cognitive performance were obtained in NC. In conclusion, cognitive effects of APOE–adAD gene interaction were differentiated between the PSEN1 and APP mutation carriers, indicating epistasis.

Omics Multi-Layers Networks Provide Novel Mechanistic and Functional Insights Into Fat Storage and Lipid Metabolism in Poultry

Fatty acid metabolism in poultry has a major impact on production and disease resistance traits. According to the high rate of interactions between lipid metabolism and its regulating properties, a holistic approach is necessary. To study omics multilayers of adipose tissue and identification of genes and miRNAs involved in fat metabolism, storage and endocrine signaling pathways in two groups of broiler chickens with high and low abdominal fat, as well as high-throughput techniques, were used. The gene–miRNA interacting bipartite and metabolic-signaling networks were reconstructed using their interactions. In the analysis of microarray and RNA-Seq data, 1,835 genes were detected by comparing the identified genes with significant expression differences (p.adjust < 0.01, fold change ≥ 2 and ≤ −2). Then, by comparing between different data sets, 34 genes and 19 miRNAs were detected as common and main nodes. A literature mining approach was used, and seven genes were identified and added to the common gene set. Module finding revealed three important and functional modules, which were involved in the peroxisome proliferator-activated receptor (PPAR) signaling pathway, biosynthesis of unsaturated fatty acids, Alzheimer’s disease metabolic pathway, adipocytokine, insulin, PI3K–Akt, mTOR, and AMPK signaling pathway. This approach revealed a new insight to better understand the biological processes associated with adipose tissue.