Neuroimaging genetic risk for Alzheimer's disease in preclinical individuals: From candidate genes to polygenic approaches

Investigating the Association Between Polygenic Risk Scores for Alzheimer’s Disease With Cognitive Performance and Intrinsic Functional Connectivity in Healthy Adults

Background

Alzheimer’s disease (AD) pathology is present many years before the onset of clinical symptoms. AD dementia cannot be treated. Timely and early detection of people at risk of developing AD is key for primary and secondary prevention. Moreover, understanding the underlying pathology that is present in the earliest stages of AD, and the genetic predisposition to that might contribute to the development of targeted disease-modifying treatments.

Objectives

In this study, we aimed to explore whether genetic disposition to AD in asymptomatic individuals is associated with altered intrinsic functional connectivity as well as cognitive performance on neuropsychological tests.

Methods

We examined 136 cognitively healthy adults (old group: mean age = 69.32, SD = 4.23; young group: mean age = 31.34, SD = 13.12). All participants had undergone resting-state functional magnetic resonance imagining (fMRI), DNA genotyping to ascertain polygenic risk scores (PRS), and neuropsychological testing for global cognition, working memory, verbal fluency, and executive functions.

Results

Two-step hierarchical regression analysis revealed that higher PRS was significantly associated with lower scores in working memory tasks [Letter Number Span: ΔR² = 0.077 (p < 0.05); Spatial Span: ΔR² = 0.072 (p < 0.05)] in older adults (>60 years). PRS did not show significant modulations of the intrinsic functional connectivity of the posterior cingulate cortex (PCC) with other regions of interest in the brain that are affected in AD.

Conclusion

Allele polymorphisms may modify the effect of other AD risk factors. This potential modulation warrants further investigations, particularly in cognitively healthy adults.

Genetic architecture of Alzheimer's disease

Advances in genetic and genomic technologies over the last thirty years have greatly enhanced our knowledge concerning the genetic architecture of Alzheimer's disease (AD). Several genes including APP, PSEN1, PSEN2, and APOE have been shown to exhibit large effects on disease susceptibility, with the remaining risk loci having much smaller effects on AD risk. Notably, common genetic variants impacting AD are not randomly distributed across the genome. Instead, these variants are enriched within regulatory elements active in human myeloid cells, and to a lesser extent liver cells, implicating these cell and tissue types as critical to disease etiology. Integrative approaches are emerging as highly effective for identifying the specific target genes through which AD risk variants act and will likely yield important insights related to potential therapeutic targets in the coming years. In the future, additional consideration of sex- and ethnicity-specific contributions to risk as well as the contribution of complex gene-gene and gene-environment interactions will likely be necessary to further improve our understanding of AD genetic architecture.

From Polygenic Scores to Precision Medicine in Alzheimer's Disease: A Systematic Review

BACKGROUND

Late-onset Alzheimer's disease (AD) is highly heritable. The effect of many common genetic variants, single nucleotide polymorphisms (SNPs), confer risk. Variants are clustered in areas of biology, notably immunity and inflammation, cholesterol metabolism, endocytosis, and ubiquitination. Polygenic scores (PRS), which weight the sum of an individual's risk alleles, have been used to draw inferences about the pathological processes underpinning AD.

OBJECTIVE

This paper aims to systematically review how AD PRS are being used to study a range of outcomes and phenotypes related to neurodegeneration.

METHODS

We searched the literature from July 2008-July 2018 following PRISMA guidelines.

RESULTS

57 studies met criteria. The AD PRS can distinguish AD cases from controls. The ability of AD PRS to predict conversion from mild cognitive impairment (MCI) to AD was less clear. There was strong evidence of association between AD PRS and cognitive impairment. AD PRS were correlated with a number of biological phenotypes associated with AD pathology, such as neuroimaging changes and amyloid and tau measures. Pathway-specific polygenic scores were also associated with AD-related biologically relevant phenotypes.

CONCLUSION

PRS can predict AD effectively and are associated with cognitive impairment. There is also evidence of association between AD PRS and other phenotypes relevant to neurodegeneration. The associations between pathway specific polygenic scores and phenotypic changes may allow us to define the biology of the disease in individuals and indicate who may benefit from specific treatments. Longitudinal cohort studies are required to test the ability of PGS to delineate pathway-specific disease activity.

Genetic Risk for Alzheimer's Disease Moderates the Association Between Medial Temporal Lobe Volume and Episodic Memory Performance Among Older Adults

BACKGROUND

A complex set of interactions between biological, genetic, and environmental factors likely underlies the development of Alzheimer's disease (AD). Identifying which of these factors is most associated with AD is important for early diagnosis and treatment.

OBJECTIVE

We sought to examine genetic risk and structural brain volume on episodic memory in a sample of older adults ranging from cognitively normal to those diagnosed with AD.

METHODS

686 adults (55-91 years old) completed a 3T MRI scan, baseline cognitive assessments, and biospecimen collection through the Alzheimer's Disease Neuroimaging Initiative. Hierarchical linear regression analyses examined main and interaction effects of medial temporal lobe (MTL) volume and polygenic hazard score (PHS), indicating genetic risk for AD, on a validated episodic memory composite score.

RESULTS

Genetic risk moderated the relationship between MTL volume and memory, such that individuals with high PHS and lower hippocampal and entorhinal volume had lower memory composite scores [ΔF (1,677) = 4.057, p = 0.044, ΔR2 = 0.002]. Further analyses showed this effect was driven by the left hippocampus [ΔF(1,677) = 5.256, p = 0.022, ΔR2 = 0.003] and right entorhinal cortex [ΔF (1,677) = 6.078, p = 0.014, ΔR2 = 0.003].

CONCLUSIONS

Among those with high genetic risk for AD, lower volume was associated with poorer memory. Results suggest that the interaction between AD genetic risk and MTL volume increases the likelihood for memory impairment among older adults. Results from this study suggest that genetic risk and brain volume should be considered key factors in tracking cognitive decline.

Functional segregation loss over time is moderated by APOE genotype in healthy elderly

We investigated the influence of the apolipoprotein E-ɛ4 allele (APOE-ɛ4) on longitudinal age-related changes in brain functional connectivity (FC) and cognition, in view of mixed cross-sectional findings. One hundred and twenty-two healthy older adults (aged 58-79; 25 APOE-ɛ4 carriers) underwent task-free fMRI scans at baseline. Seventy-eight (16 carriers) had at least one follow-up (every 2 years). Changes in intra- and internetwork FCs among the default mode (DMN), executive control (ECN), and salience (SN) networks, as well as cognition, were quantified using linear mixed models. Cross-sectionally, APOE-ɛ4 carriers had lower functional connectivity between the ECN and SN than noncarriers. Carriers also showed a stronger age-dependent decrease in visuospatial memory performance. Longitudinally, carriers had steeper increase in inter-ECN-DMN FC, indicating loss of functional segregation. The longitudinal change in processing speed performance was not moderated by APOE-ɛ4 genotype, but the brain-cognition association was. In younger elderly, faster loss of segregation was correlated with greater decline in processing speed regardless of genotype. In older elderly, such relation remained for noncarriers but reversed for carriers. APOE-ɛ4 may alter aging by accelerating the change in segregation between high-level cognitive systems. Its modulation on the longitudinal brain-cognition relationship was age-dependent.

Late-Onset Alzheimer's Disease Polygenic Risk Profile Score Predicts Hippocampal Function

BACKGROUND

We explored the cumulative effect of several late-onset Alzheimer's disease (LOAD) risk loci using a polygenic risk profile score (RPS) approach on measures of hippocampal function, cognition, and brain morphometry.

METHODS

In a sample of 231 healthy control subjects (19-55 years of age), we used an RPS to study the effect of several LOAD risk loci reported in a recent meta-analysis on hippocampal function (determined by its engagement with blood oxygen level-dependent functional magnetic resonance imaging during episodic memory) and several cognitive metrics. We also studied effects on brain morphometry in an overlapping sample of 280 subjects.

RESULTS

There was almost no significant association of LOAD-RPS with cognitive or morphometric measures. However, there was a significant negative relationship between LOAD-RPS and hippocampal function (familywise error [small volume correction-hippocampal region of interest] p < .05). There were also similar associations for risk score based on APOE haplotype, and for a combined LOAD-RPS + APOE haplotype risk profile score (p < .05 familywise error [small volume correction-hippocampal region of interest]). Of the 29 individual single nucleotide polymorphisms used in calculating LOAD-RPS, variants in CLU, PICALM, BCL3, PVRL2, and RELB showed strong effects (p < .05 familywise error [small volume correction-hippocampal region of interest]) on hippocampal function, though none survived further correction for the number of single nucleotide polymorphisms tested.

CONCLUSIONS

There is a cumulative deleterious effect of LOAD risk genes on hippocampal function even in healthy volunteers. The effect of LOAD-RPS on hippocampal function in the relative absence of any effect on cognitive and morphometric measures is consistent with the reported temporal characteristics of LOAD biomarkers with the earlier manifestation of synaptic dysfunction before morphometric and cognitive changes.

Metabolomic-guided discovery of Alzheimer's disease biomarkers from body fluid

The rapid increase in the older population has made age-related diseases like Alzheimer's disease (AD) a global concern. Given that there is still no cure for this neurodegenerative disease, the drastic growth in the number of susceptible individuals represents a major emerging threat to public health. The poor understanding of the mechanisms underlying AD is deemed the greatest stumbling block against progress in definitive diagnosis and management of this disease. There is a dire need for biomarkers that can facilitate early diagnosis, classification, prognosis, and treatment response. Efforts have been directed toward discovery of reliable and distinctive AD biomarkers but with very little success. With the recent emergence of high-throughput technology that is able to collect and catalogue vast datasets of small metabolites, metabolomics offers hope for a better understanding of AD and subsequent identification of biomarkers. This review article highlights the potential of using multiple metabolomics platforms as useful means in uncovering AD biomarkers from body fluids. © 2017 Wiley Periodicals, Inc.

An Alzheimer's Disease Genetic Risk Score Predicts Longitudinal Thinning of Hippocampal Complex Subregions in Healthy Older Adults

Variants at 21 genetic loci have been associated with an increased risk for Alzheimer's disease (AD). An important unresolved question is whether multiple genetic risk factors can be combined to increase the power to detect changes in neuroimaging biomarkers for AD. We acquired high-resolution structural images of the hippocampus in 66 healthy, older human subjects. For 45 of these subjects, longitudinal 2-year follow-up data were also available. We calculated an additive AD genetic risk score for each participant and contrasted this with a weighted risk score (WRS) approach. Each score included APOE (apolipoprotein E), CLU (clusterin), PICALM (phosphatidylinositol binding clathrin assembly protein), and family history of AD. Both unweighted risk score (URS) and WRS correlated strongly with the percentage change in thickness across the whole hippocampal complex (URS: r = -0.40; p = 0.003; WRS: r = -0.25, p = 0.048), driven by a strong relationship to entorhinal cortex thinning (URS: r = -0.35; p = 0.009; WRS: r = -0.35, p = 0.009). By contrast, at baseline the risk scores showed no relationship to thickness in any hippocampal complex subregion. These results provide compelling evidence that polygenic AD risk scores may be especially sensitive to structural change over time in regions affected early in AD, like the hippocampus and adjacent entorhinal cortex. This work also supports the paradigm of studying genetic risk for disease in healthy volunteers. Together, these findings will inform clinical trial design by supporting the idea that genetic prescreening in healthy control subjects can be useful to maximize the ability to detect an effect on a longitudinal neuroimaging endpoint, like hippocampal complex cortical thickness.