Large multi-ethnic genetic analyses of amyloid imaging identify new genes for Alzheimer disease

Abstract

Amyloid PET imaging has been crucial for detecting the accumulation of amyloid beta (Aβ) deposits in the brain and to study Alzheimer’s disease (AD). We performed a genome-wide association study on the largest collection of amyloid imaging data (N = 13,409) to date, across multiple ethnicities from multicenter cohorts to identify variants associated with brain amyloidosis and AD risk. We found a strong APOE signal on chr19q.13.32 (top SNP: APOE ɛ4; rs429358; β = 0.35, SE = 0.01, P = 6.2 × 10–311, MAF = 0.19), driven by APOE ɛ4, and five additional novel associations (APOE ε2/rs7412; rs73052335/rs5117, rs1081105, rs438811, and rs4420638) independent of APOE ɛ4. APOE ɛ4 and ε2 showed race specific effect with stronger association in Non-Hispanic Whites, with the lowest association in Asians. Besides the APOE, we also identified three other genome-wide loci: ABCA7 (rs12151021/chr19p.13.3; β = 0.07, SE = 0.01, P = 9.2 × 10–09, MAF = 0.32), CR1 (rs6656401/chr1q.32.2; β = 0.1, SE = 0.02, P = 2.4 × 10–10, MAF = 0.18) and FERMT2 locus (rs117834516/chr14q.22.1; β = 0.16, SE = 0.03, P = 1.1 × 10–09, MAF = 0.06) that all colocalized with AD risk. Sex-stratified analyses identified two novel female-specific signals on chr5p.14.1 (rs529007143, β = 0.79, SE = 0.14, P = 1.4 × 10–08, MAF = 0.006, sex-interaction P = 9.8 × 10–07) and chr11p.15.2 (rs192346166, β = 0.94, SE = 0.17, P = 3.7 × 10–08, MAF = 0.004, sex-interaction P = 1.3 × 10–03). We also demonstrated that the overall genetic architecture of brain amyloidosis overlaps with that of AD, Frontotemporal Dementia, stroke, and brain structure-related complex human traits. Overall, our results have important implications when estimating the individual risk to a population level, as race and sex will needed to be taken into account. This may affect participant selection for future clinical trials and therapies.

Genetics of Alzheimer’s Disease in the African American Population

“…The most significant associations in the AA families were observed for HV with rs3917854 near F5 and SELP ( p = 5.0 × 10 −6 ) and rs17148741 in PICALM ( p = 9.39 × 10 −5 ) and for cerebral volume with rs935793 in SYNPR ( p = 7.12 × 10 −5 ). A recent multi-ancestry GWAS of PET-amyloid imaging included an African-ancestry cohort ( n = 359) [ 101 ]. While most of the loci implicated in the joint analysis were likely accounted for the much larger EUR cohort ( n > 11,000), the African-ancestry cohort analysis yielded one GWS association with rs2271774 near PTDS1 ( p = 2.25 × 10 −9 ).…”

The ABC's of Alzheimer risk gene ABCA7

“…for their association with AD endophenotypes, such as amyloid deposition, tau pathology, brain morphology, and various clinical symptoms, which has been extensively reviewed before. 38,50 Shortly, multiple genetic markers were associated with increased amyloid pathology, which has been replicated in several studies, 38,[51][52][53][54] which could be indicative for a role of ABCA7 dysfunction in the amyloid pathway. Evidence for association with tau pathology has been more inconsistent.…”

Harmonization of CSF and imaging biomarkers for Alzheimer’s disease biomarkers: need and practical applications for genetics studies and preclinical classification

“…By comparing the GWAS summary statistics of imaging data from ADNI and Knight ADRC cohort, we have also shown that these standardized values lead to the same results as raw endophenotypes based analysis. We have successfully used the same approach in multiple studies before 15,17,25,48 provides an ideal framework for normalizing the within-and across-cohort variation in the raw endophenotypic data without masking its inherent biological characteristics. One may argue the some of the positive attributes of z-scores highlighted here are shared with the log transformation performed prior to the standardization, but the uniformity of variance across dissimilar dataset that allows for the use of the diverse biomarker data as a continuous trait is inherent to Z-score and cannot be achieved through log normalization in itself.…”

“…Z-score based data standardization approach has been previously used in several studies focused on identifying genetic variants associated with CSF and amyloid imaging 15,17,[22][23][24][25] .…”