LeBorgne J, Gomez L, Heikkinen S, Amin N, Ahmad S, Choi SH, Bis J, Grenier-Boley B, Rodriguez OG, Kleineidam L, Young J, Tripathi KP, Wang L, Varma A, vanderLee S, Damotte V, deRojas I, Palmal S, EADB, GR@ACE, DEGESCO, EADI, GERAD, DemGene, FinnGen, ADGC, CHARGE, Giedraitis V, Ghidoni R, Fernandez V, Kehoe PG, Frikke-Schmidt R, Tsolaki M, Sanchez-Juan P, Sleegers K, Ingelsson M, Haines J, Farrer L, Mayeux R, Wang L-S, Sims R, DeStefano A, Schellenberg GD, Seshadri S, Amouyel P, Wil. X-chromosome-wide association study for Alzheimer's disease. 2024 May 03 10.1101/2024.05.02.24306739 (version 1) medRxiv.
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University of California, San Francisco
In their timely and well-executed study, Belloy et al. conducted a large-scale X-chromosome-wide association study of the genetics of Alzheimer’s disease. Their approach is novel and much-anticipated because the X chromosome has been largely excluded in genome-wide studies due to technical challenges, despite the high relevance of X-linked genes in the brain and in neurological conditions. Those technical challenges have been related to X hemizygosity in male individuals, random X inactivation and baseline X escape in female individuals, shared sequences between the X and Y, and limited representation of the X on SNP arrays. Expanding tool kits in genome-wide association studies, alongside other sequencing approaches in examining the X, are advancing a dedicated study of this sex chromosome and leading to potentially meaningful discoveries.
Analysis of over one million individuals revealed four loci with genome-wide significance, with a lead variant within SLC9A7, a transporter molecule that contributes to pH homeostasis within the Golgi apparatus. It will be particularly interesting to know how genetic variation alters cell type-specific SLC9A7 levels and function, and how that links to AD risk—an important mechanistic charge for basic and translational bench research.
It is notable that the two similar studies, while significantly smaller, also report X-chromosome wide signals. Collectively, these studies highlight the high value of the X as a contributor to neural-related functions and as a source of sex difference.
While genetic variation of the X chromosome is an important broad-stroke approach to examining this sex chromosome, X biology may contribute to risk and resilience of AD in several ways, including through gene expression and epigenetic alterations. This is particularly important because females harbor two X chromosomes, and while one is epigenetically inactivated compared to males, the “silent X” partially escapes inactivation and therefore increases the “dose” of the X in females.
In up-and-coming advances, we will understand more about how aging and Alzheimer’s modulate the inactive X, and how that influences sex-based risk and resilience. At the end of the day, the new XWASes and other X studies are pivotal because they could pave the way to new therapeutic targets that benefit men, women, or both sexes.
View all comments by Dena DubalUniversity of Lille, Inserm, Institute Pasteur Lille
Belloy et al. performed an XWAS for AD by analyzing 15,081 clinical-AD cases, 41,091 registry-AD and Alzheimer’s disease and dementia (ADD) cases and 82,386 proxy-ADD cases. They identified a genome-wide significant (P<5x10-8) signal in the SLC9A7 locus, with a low effect size (OR=1.054 (1.035-1.075)). They additionally identified five X-chromosome-wide significant (defined as P < 1x10-5) signals. This work addresses an important gap in the genetics of AD, as the X chromosome was excluded from the large-scale GWAS on AD.
In the European Alzheimer & Dementia Biobank (EADB), the International Genomics of Alzheimer’s Project (IGAP), and two biobanks, we also performed a large-scale XWAS for AD on 52,214 clinical-AD cases, 7,759 registry-AD cases and 55,868 proxy-ADD cases. Even though we considered two additional models of X-chromosome inactivation compared to the Belloy study, we did not identify any genome-wide significant signals, but did identify seven X-chromosome-wide significant loci, considering a stricter threshold of P ≤ 1.6×10−6 than did Belloy et al.
However, the loci we and Belloy identified do not overlap. Though we both found signals in the NLGN4X region, they are different: the two index variants (rs150798997 in Belloy et al., rs4364769 in our study) are located 270,925 bp away, and there is no linkage disequilibrium as determined in the EADB-core dataset. It is noteworthy that, even if we do not replicate the signal seen by Belloy at the SLC9A7 index variant (P=1.36x10-2), we did observe a signal in the locus at another variant, but with a lower absolute effect size than in (P=5.2x10-5).
The lack of overlap between the two studies could be due to several reasons, including:
a) some of the loci are false positives; a higher rate of false positives is expected among signals with X-chromosome-wide significance rather than genome-wide significance;
b) the winner’s curse: signals are expected to be slightly inflated in the first study which identified them;
c) a difference in power;
d) the phenotype definition. The proportion of clinical-AD, registry-AD, registry-ADD and proxy-ADD cases is very different between the two studies. Considering that four proxy cases effectively provide the same power as one diagnosed case, the clinical-AD, registry-AD/ADD, and proxy-ADD cases represent 20 percent, 54 percent, and 27 percent, respectively, of the effective number of cases in Belloy et al study, but 71 percent, 10 percent, and 19 percent in our study. Since a higher proportion of non-AD dementia cases is expected in the registry and proxy-ADD cases, this could lead to different genetic signals. Additionally, the proxy-ADD cases definition also differs in the two studies.
In conclusion, these XWAS did not find common genetic risk factors of large effect for AD on the non-pseudoautosomal region of the X-chromosome but identified signals which warrant further investigations, in particular to delineate their impact on AD versus ADD risk. Also, both studies were based on genotyping data, which leads to technical difficulties—for example lower coverage, in particular of the X-chromosome pseudoautosomal regions, lower call rate or lower imputation quality compared to autosomes. Future analyses of sequencing data will help to address some of those issues, and will allow to study the impact of X-chromosome rare or structural variants on AD risk.
View all comments by Céline BellenguezMake a Comment
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