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Biomedical subjects

Caroline Jonson

Publications and source records attributed to Caroline Jonson.

3 recordsLinked to original sources

APOE-stratified genome-wide association analyses provide insights into the genetic etiology of Alzheimers's disease.

Among the more than 90 identified genetic risk loci for late-onset Alzheimer's disease (AD) and related dementias, the apolipoprotein E (APOE) gene ɛ2/ɛ3/ɛ4 polymorphisms remain the longstanding benchmark for genetic disease risk with a consistently large effect across studies1-10. Despite this massive signal, the exact mechanisms by which ɛ4 increases and ɛ2 decreases dementia risk remain poorly understood. Notably, recent trials of anti-amyloid therapies suggest less efficacy and higher risks of severe side effects in ε4 carriers11-13, hampering the treatment of those with the highest unmet need. To improve our understanding of the genetic architecture of AD in the context of its main genetic driver, we performed genome-wide association studies (GWASs) stratified by ε4 and ε2 carrier status. HP1BP3, SLC50A1, PTPRC, NPAS3, DDHD1, CHST9, SMYD2, PRAMEF1 and GFRA1 emerged as new genomic signals for AD risk, appearing only when stratified by APOE carrier status. DDHD1 appeared especially promising, showing protective effects in ε4 carriers, being identified as an expression quantitative trait locus and being involved in rare neuronal diseases. Such APOE-stratified insights may help understand and overcome side effects, inform clinical trial enrollment strategies, and create the scientific basis for targeted, mechanism-driven therapies in neurodegenerative diseases.

Journal Article

Evaluating the causal effect of mitochondrial dysfunction on Alzheimer's and Parkinson's disease using Polygenic Risk Scores and Mendelian Randomization.

INTRODUCTION: Mitochondrial DNA copy number (mtDNAcn), a measure of mitochondrial genomes per nucleated cell, has an unclear causal relationship with AD and PD. We integrate genetic correlation, Polygenic Risk Scores (PRS), and Mendelian Randomization (MR) to assess whether mtDNAcn influences the risk of AD and PD, and evaluate how study-specific factors in mtDNAcn genome-wide association studies (GWAS) may distort these causal estimates. METHODS: Using GWAS of four mtDNAcn measures, AD, AD/dementia, and PD, we evaluated genetic correlations, generated ancestry-normalized PRS in the AD Genetics Consortium (N=27,383), and applied MR methods including Latent Heritable Confounder MR (LHC-MR). RESULTS: Across the four mtDNAcn GWAS, only one was consistently associated with AD/dementia and PD, with genetic correlations and PRS analysis showing negative correlations and MR indicating that higher mtDNAcn reduced AD/dementia and PD risk. DISCUSSION: Higher blood-based mtDNAcn was causally associated with reduced risk of AD/dementia and PD, with limited evidence to suggest a bidirectional effect.

Alzheimer’s disease

The Role of Genomic-Informed Risk Assessments in Predicting Dementia Outcomes.

INTRODUCTION: By integrating genetic and clinical risk factors into genomic-informed dementia risk reports, healthcare providers can offer patients detailed risk profiles to facilitate understanding of individual risk and support the implementation of personalized strategies for promoting brain health. METHODS: We constructed an additive score comprising the modified Cardiovascular Risk Factors, Aging, and Incidence of Dementia Risk Score (mCAIDE), family history of dementia, APOE genotype, and an AD polygenic risk score in NACC and ADNI, and assessed its association with progression to all-cause dementia. RESULTS: 81% of participants had at least one high-risk indicator for dementia, with each additional risk indicator linked to a 34% increase in the hazard of dementia onset. DISCUSSION: We found that most participants in memory and aging clinics had at least one high-risk indicator for dementia. Furthermore, we observed a dose-response relationship where a greater number of risk indicators was associated with an increased risk of incident dementia.

dementia risk scores