Genetic data and cognitively defined late-onset Alzheimer’s disease subgroups

Abstract

Categorizing people with late-onset Alzheimer’s disease into biologically coherent subgroups is important for personalized medicine. We evaluated data from five studies (total n = 4050, of whom 2431 had genome-wide single-nucleotide polymorphism (SNP) data). We assigned people to cognitively defined subgroups on the basis of relative performance in memory, executive functioning, visuospatial functioning, and language at the time of Alzheimer’s disease diagnosis. We compared genotype frequencies for each subgroup to those from cognitively normal elderly controls. We focused on APOE and on SNPs with p < 10−5 and odds ratios more extreme than those previously reported for Alzheimer’s disease (<0.77 or >1.30). There was substantial variation across studies in the proportions of people in each subgroup. In each study, higher proportions of people with isolated substantial relative memory impairment had ≥1 APOE ε4 allele than any other subgroup (overall p = 1.5 × 10−27). Across subgroups, there were 33 novel suggestive loci across the genome with p < 10−5 and an extreme OR compared to controls, of which none had statistical evidence of heterogeneity and 30 had ORs in the same direction across all datasets. These data support the biological coherence of cognitively defined subgroups and nominate novel genetic loci.

Clustering by phenotype and genome-wide association study in autism

“…Previous studies regarding Alzheimer's disease, neuroticism, or asthma found that items or symptoms showed, to some degree, increased ORs between the case loci and control loci compared to those from previous studies using broadly defined disease diagnoses (9)(10)(11). These findings may indicate that GWAS based on a symptom or an item could identify genetically more homogeneous subgroups and let us hypothesize that a relatively reasonable combination of symptoms or items could identify more genetically homogeneous subgroups.…”

“…First, Chaste and colleagues used one item or symptom alone, whereas we used combinations of them with a machine learning method. DeMichele-Sweet and colleagues reported that subgrouping only by having psychosis could lead to the identification of limited loci that had small effects (59), but Mukherjee and colleagues found a substantial number of suggestive loci that had extreme ORs after categorizing persons with Alzheimer's disease based on relative performance across cognitive domains by modern psychometric approaches (9). It may be necessary to utilize an appropriate combination of data to reveal masked patterns of data sets.…”

“…Traylor and colleagues (8) demonstrated that attempts to categorize patients with a complex disease into more homogeneous subgroups could have more power to elucidate the hidden heritability in a simulation study. Several studies on Alzheimer's disease, neuroticism, or asthma indicated that items or symptoms were to some degree more useful for identifying high-impact genetic factors than broadly defined diagnoses (9)(10)(11), although a study of ASD demonstrated modest effects of two-way stratification by individual symptoms (12). Additionally, medical researchers have begun to use machine learning methods (13), which is an artificial intelligence technique that can reveal masked patterns of data sets.…”

Biobank-wide association scan identifies risk factors for late-onset Alzheimer’s disease and endophenotypes

“…First, we tested the associations between the 48 PRSs for AD-associated traits and five AD subgroups defined in the Executive Prominent Alzheimer’s Disease (EPAD) study of cognitively-defined AD subgroups, i.e. isolated relative impairments in memory, language, and visuospatial functioning, no domain with an isolated relative impairment, and multiple domains with relative impairments ( Methods ) [21, 22]. The PRS for maternal family history of AD and dementia was strongly and consistently associated with all five cognitively defined AD subgroups ( Supplementary Table 8 ), with the group with isolated relative memory impairment showing the strongest association (p=3.3e-16), which is consistent with the higher frequency of APOE ε 4 in this subgroup [21].…”

Transcriptomic Stratification of Late-Onset Alzheimer’s Cases Reveals Novel Genetic Modifiers of Disease Pathology

“…We also assessed the rate of decline in memory, executive function, visuospatial function, and language across the subtypes. Definitions, collection, and standardization of these decline measures can be found in previously published work 24 .…”