KIBRA T allele influences memory performance and progression of cognitive decline: a 7-year follow-up study in subjective cognitive decline and mild cognitive impairment

Subjective Cognitive Decline and Genetic Propensity for Dementia beyond Apolipoprotein ε4: A Systematic Review

Subjective cognitive decline (SCD) has been described as a probable early stage of dementia, as it has consistently appeared to precede the onset of objective cognitive impairment. SCD is related to many risk factors, including genetic predisposition for dementia. The Apolipoprotein (APOE) ε4 allele, which has been thoroughly studied, seems to explain genetic risk for SCD only partially. Therefore, we aimed to summarize existing data regarding genetic factors related to SCD, beyond APOE ε4, in order to improve our current understanding of SCD. We conducted a PRISMA systematic search in PubMed/MEDLINE and Embase databases using the keywords "subjective cognitive decline" and "genetic predisposition" with specific inclusion and exclusion criteria. From the 270 articles identified, 16 were finally included for the qualitative analysis. Family history of Alzheimer's disease (AD) in regard to SCD was explored in eight studies, with conflicting results. Other genes implicated in SCD, beyond APOE ε4, were investigated in six studies, which were not strong enough to provide clear conclusions. Very few data have been published regarding the association of polygenic risk for AD and SCD. Thus, many more genes related to AD must be studied, with polygenic risk scores appearing to be really promising for future investigation.

Machine Learning Approach to Identify Case-Control Studies on ApoE Gene Mutations Linked to Alzheimer’s Disease in Italy

Background: An application of artificial intelligence is machine learning, which allows computer programs to learn and create data. Methods: In this work, we aimed to evaluate the performance of the MySLR machine learning platform, which implements the Latent Dirichlet Allocation (LDA) algorithm in the identification and screening of papers present in the literature that focus on mutations of the apolipoprotein E (ApoE) gene in Italian Alzheimer’s Disease patients. Results: MySLR excludes duplicates and creates topics. MySLR was applied to analyze a set of 164 scientific publications. After duplicate removal, the results allowed us to identify 92 papers divided into two relevant topics characterizing the investigated research area. Topic 1 contains 70 papers, and topic 2 contains the remaining 22. Despite the current limitations, the available evidence suggests that articles containing studies on Italian Alzheimer’s Disease (AD) patients were 65.22% (n = 60). Furthermore, the presence of papers about mutations, including single nucleotide polymorphisms (SNPs) ApoE gene, the primary genetic risk factor of AD, for the Italian population was 5.4% (n = 5). Conclusion: The results show that the machine learning platform helped to identify case-control studies on ApoE gene mutations, including SNPs, but not only conducted in Italy.

Genetic analyses in multiplex families confirms chromosome 5q35 as a risk locus for Alzheimer's Disease in individuals of African Ancestry

There is a paucity of genetic studies of Alzheimer Disease (AD) in individuals of African Ancestry, despite evidence suggesting increased risk of AD in the African American (AA) population. We performed whole-genome sequencing (WGS) and multipoint linkage analyses in 51 multi-generational AA AD families ascertained through the Research in African American Alzheimer Disease Initiative (REAAADI) and the National Institute on Aging Late Onset Alzheimer's disease (NIA-LOAD) Family Based Study. Variants were prioritized on minor allele frequency (<0.01), functional potential of coding and noncoding variants, co-segregation with AD and presence in multi-ancestry ADSP release 3 WGS data. We identified a significant linkage signal on chromosome 5q35 (HLOD=3.3) driven by nine families. Haplotype segregation analysis in the family with highest LOD score identified a 3'UTR variant in INSYN2B with the most functional evidence. Four other linked AA families harbor within-family shared variants located in INSYN2B's promoter or enhancer regions. This AA family-based finding shows the importance of diversifying population-level genetic data to better understand the genetic determinants of AD on a global scale.

PRedicting the EVolution of SubjectIvE Cognitive Decline to Alzheimer's Disease With machine learning: the PREVIEW study protocol

BACKGROUND

As disease-modifying therapies (DMTs) for Alzheimer's disease (AD) are becoming a reality, there is an urgent need to select cost-effective tools that can accurately identify patients in the earliest stages of the disease. Subjective Cognitive Decline (SCD) is a condition in which individuals complain of cognitive decline with normal performances on neuropsychological evaluation. Many studies demonstrated a higher prevalence of Alzheimer's pathology in patients diagnosed with SCD as compared to the general population. Consequently, SCD was suggested as an early symptomatic phase of AD. We will describe the study protocol of a prospective cohort study (PREVIEW) that aim to identify features derived from easily accessible, cost-effective and non-invasive assessment to accurately detect SCD patients who will progress to AD dementia.

METHODS

We will include patients who self-referred to our memory clinic and are diagnosed with SCD. Participants will undergo: clinical, neurologic and neuropsychological examination, estimation of cognitive reserve and depression, evaluation of personality traits, APOE and BDNF genotyping, electroencephalography and event-related potential recording, lumbar puncture for measurement of Aβ42, t-tau, and p-tau concentration and Aβ42/Aβ40 ratio. Recruited patients will have follow-up neuropsychological examinations every two years. Collected data will be used to train a machine learning algorithm to define the risk of being carriers of AD and progress to dementia in patients with SCD.

DISCUSSION

This is the first study to investigate the application of machine learning to predict AD in patients with SCD. Since all the features we will consider can be derived from non-invasive and easily accessible assessments, our expected results may provide evidence for defining cost-effective and globally scalable tools to estimate the risk of AD and address the needs of patients with memory complaints. In the era of DMTs, this will have crucial implications for the early identification of patients suitable for treatment in the initial stages of AD.

TRIAL REGISTRATION NUMBER (TRN)

NCT05569083.

Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer's Disease continuum?

Alzheimer's disease (AD) pathological changes may begin up to decades earlier than the appearance of the first symptoms of cognitive decline. Subjective cognitive decline (SCD) could be the first pre-clinical sign of possible AD, which might be followed by mild cognitive impairment (MCI), the initial stage of clinical cognitive decline. However, the neural correlates of these prodromic stages are not completely clear yet. Recent studies suggest that EEG analysis tools characterizing the cortical activity as a whole, such as microstates and cortical regions connectivity, might support a characterization of SCD and MCI conditions. Here we test this approach by performing a broad set of analyses to identify the prominent EEG markers differentiating SCD (n = 57), MCI (n = 46) and healthy control subjects (HC, n = 19). We found that the salient differences were in the temporal structure of the microstates patterns, with MCI being associated with less complex sequences due to the altered transition probability, frequency and duration of canonic microstate C. Spectral content of EEG, network connectivity, and spatial arrangement of microstates were instead largely similar in the three groups. Interestingly, comparing properties of EEG microstates in different cerebrospinal fluid (CSF) biomarkers profiles, we found that canonic microstate C displayed significant differences in topography in AD-like profile. These results show that the progression of dementia might be associated with a degradation of the cortical organization captured by microstates analysis, and that this leads to altered transitions between cortical states. Overall, our approach paves the way for the use of non-invasive EEG recordings in the identification of possible biomarkers of progression to AD from its prodromal states.

Thalamic gray matter volume mediates the association between KIBRA polymorphism and olfactory function among older adults: a population-based study

The kidney and brain expressed protein (KIBRA) rs17070145 polymorphism is associated with both structure and activation of the olfactory cortex. However, no studies have thus far examined whether KIBRA can be linked with olfactory function and whether brain structure plays any role in the association. We addressed these questions in a population-based cross-sectional study among rural-dwelling older adults. This study included 1087 participants derived from the Multidomain Interventions to Delay Dementia and Disability in Rural China, who underwent the brain MRI scans in August 2018 to October 2020; of these, 1016 took the 16-item Sniffin' Sticks identification test and 634 (62.40%) were defined with olfactory impairment (OI). Data were analyzed using the voxel-based morphometry analysis and general linear, logistic, and structural equation models. The KIBRA rs17070145 C-allele (CC or CT vs. TT genotype) was significantly associated with greater gray matter volume (GMV) mainly in the bilateral orbitofrontal cortex and left thalamus (P < 0.05) and with the multi-adjusted odds ratio of 0.73 (95% confidence interval 0.56-0.95) for OI. The left thalamic GMV could mediate 8.08% of the KIBRA-olfaction association (P < 0.05). These data suggest that the KIBRA rs17070145 C-allele is associated with a reduced likelihood of OI among older adults, partly mediated through left thalamic GMV.

The Effect of CAG Repeats within the Non-Pathological Range in the HTT Gene on Cognitive Functions in Patients with Subjective Cognitive Decline and Mild Cognitive Impairment

The Huntingtin gene (HTT) is within a class of genes containing a key region of CAG repeats. When expanded beyond 39 repeats, Huntington disease (HD) develops. Individuals with less than 35 repeats are not associated with HD. Increasing evidence has suggested that CAG repeats play a role in modulating brain development and brain function. However, very few studies have investigated the effect of CAG repeats in the non-pathological range on cognitive performances in non-demented individuals. In this study, we aimed to test how CAG repeats' length influences neuropsychological scores in patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI). We included 75 patients (46 SCD and 29 MCI). All patients underwent an extensive neuropsychological battery and analysis of HTT alleles to quantify the number of CAG repeats. Results: CAG repeat number was positively correlated with scores of tests assessing for executive function, visual-spatial ability, and memory in SCD patients, while in MCI patients, it was inversely correlated with scores of visual-spatial ability and premorbid intelligence. When we performed a multiple regression analysis, we found that these relationships still remained, also when adjusting for possible confounding factors. Interestingly, logarithmic models better described the associations between CAG repeats and neuropsychological scores. CAG repeats in the HTT gene within the non-pathological range influenced neuropsychological performances depending on global cognitive status. The logarithmic model suggested that the positive effect of CAG repeats in SCD patients decreases as the number of repeats grows.

Dual Effect of PER2 C111G Polymorphism on Cognitive Functions across Progression from Subjective Cognitive Decline to Mild Cognitive Impairment

BACKGROUND

Periodic circadian protein homolog 2 (PER2) has a role in the intracellular signaling pathways of long-term potentiation and has implications for synaptic plasticity. We aimed to assess the association of PER2 C111G polymorphism with cognitive functions in subjective cognitive decline (SCD).

METHODS

Forty-five SCD patients were included in this study. All participants underwent extensive neuropsychological investigation, analysis of apolipoprotein E (APOE) and PER2 genotypes, and neuropsychological follow-up every 12 or 24 months for a mean time of 9.87 ± 4.38 years.

RESULTS

Nine out of 45 patients (20%) were heterozygous carriers of the PER2 C111G polymorphism (G carriers), while 36 patients (80%) were not carriers of the G allele (G non-carriers). At baseline, G carriers had a higher language composite score compared to G non-carriers. During follow-up, 15 (34.88%) patients progressed to mild cognitive impairment (MCI). In this group, we found a significant interaction between PER2 G allele and follow-up time, as carriers of G allele showed greater worsening of executive function, visual-spatial ability, and language composite scores compared to G non-carriers.

CONCLUSIONS

PER2 C111G polymorphism is associated with better language performance in SCD patients. Nevertheless, as patients progress to MCI, G allele carriers showed a greater worsening in cognitive performance compared to G non-carriers. The effect of PER2 C111G polymorphism depends on the global cognitive status of patients.

Neuroimaging advances regarding subjective cognitive decline in preclinical Alzheimer's disease

Subjective cognitive decline (SCD) is regarded as the first clinical manifestation in the Alzheimer’s disease (AD) continuum. Investigating populations with SCD is important for understanding the early pathological mechanisms of AD and identifying SCD-related biomarkers, which are critical for the early detection of AD. With the advent of advanced neuroimaging techniques, such as positron emission tomography (PET) and magnetic resonance imaging (MRI), accumulating evidence has revealed structural and functional brain alterations related to the symptoms of SCD. In this review, we summarize the main imaging features and key findings regarding SCD related to AD, from local and regional data to connectivity-based imaging measures, with the aim of delineating a multimodal imaging signature of SCD due to AD. Additionally, the interaction of SCD with other risk factors for dementia due to AD, such as age and the Apolipoprotein E (ApoE) ɛ4 status, has also been described. Finally, the possible explanations for the inconsistent and heterogeneous neuroimaging findings observed in individuals with SCD are discussed, along with future directions. Overall, the literature reveals a preferential vulnerability of AD signature regions in SCD in the context of AD, supporting the notion that individuals with SCD share a similar pattern of brain alterations with patients with mild cognitive impairment (MCI) and dementia due to AD. We conclude that these neuroimaging techniques, particularly multimodal neuroimaging techniques, have great potential for identifying the underlying pathological alterations associated with SCD. More longitudinal studies with larger sample sizes combined with more advanced imaging modeling approaches such as artificial intelligence are still warranted to establish their clinical utility.