X-Chromosome-Wide Association Data Spot Alzheimer’s Loci

About two-thirds of people with Alzheimer’s disease are women, yet due to the challenges in studying X chromosomes, a genetic foundation for this has been difficult to uncover. Now, two large X-chromosome-wide association studies (XWAS) and a smaller one based on pathologically confirmed AD identify 12 loci that might shed some light on the matter.

  • One study included data from more than 1 million people.
  • It pegged a variant in SLC9A7 that boosts AD risk by 5 percent.
  • The variant may ramp up Aβ production by disrupting pH in the Golgi.

In the September 9 JAMA Neurology, scientists led by Michael Belloy, Washington University in St. Louis, report four common and two rare variants on the X chromosome that associate with AD. This follows an XWAS uploaded to medRxiv May 3, in which an international group led by Céline Bellenguez, University of Lille, France, identified four different loci, and a paper published September 4 in Translational Psychiatry describing two more that were uncovered by Valentina Escott-Price, Cardiff University, U.K., and her colleagues.

Of these 12 loci, only one, near the SLC9A7 gene, reached genome-wide significance. The other 11 were significant at the chromosome-wide level and warrant further study, scientists say. In association studies, scientist consider variants that pass genome-wide significance as “hits,” and those that pass the less-stringent chromosome-wide test as “suggestive.”

“The new XWASes and other X chromosome studies are pivotal because they could pave the way for new therapeutic targets that benefit men, women, or both sexes,” wrote Dena Dubal of the University of California, San Francisco, who was not involved in any of the studies.

The X chromosome contains about 1,200 genes. “This is 5 percent of the genome that has been dark to us,” Belloy told Alzforum. This chromosome is typically omitted from GWAS because it complicates statistical analyses. In women, most genes on one of these two chromosomes are inactivated during early embryonic development to avoid double-dosing. Some genes escape this inactivation, however, and this is unpredictable and can change during life (see Peeters et al., 2023, for a review). 

Belloy and his colleagues parsed the genomes of more than 1,100,000 people, including women and men with AD, their first-degree relatives, as well as healthy controls, to look for variants that associate with AD. The dataset, which included cohorts from the Alzheimer’s Disease Genetics Consortium, Alzheimer’s Disease Sequencing Project, U.K. Biobank (UKB), Finnish health registry (FinnGen), and U.S. Million Veterans Program (MVP), yielded six independent genetic variants—four could be tied to the regulation of nearby genes.

Of the six, one, a single-nucleotide variation in an intron of SLC9A7 stood out. The variant not only exceeded the statistical significance threshold for genome-wide association, but, mechanistically, the SLC9A7 gene might promote Aβ production.

X Factors. Manhattan plot of XWAS meta-analysis shows two rare and four common variants linked to AD. SLC9A7 passed a conservative genome-wide significance threshold (upper horizontal line). The others passed the threshold for X-chromosome-wide significance, a less stringent bar (lower line). [Courtesy of Belloy et al., 2024.]

Previously, scientists led by coauthor Joachim Herz at the University of Texas Southwestern Medical Center in Dallas had reported that greater expression of the sodium-hydrogen exchanger NHE6, encoded by the SLC9A7 ortholog SLC9A6, triggers ApoE aggregation, which in turn leads to Aβ accumulation (see Jul 2021 news; Pohlkamp et al., 2021). NHEs function in cellular homeostasis. Blocking NHE6 restored acidification of the early endosomal compartment and suppressed amyloid accumulation, Herz found.

Both SLC9A6 and SLC9A7 are highly conserved across species. “Although their functions aren't exactly the same, they are closely related,” Belloy said. These exchangers regulate the pH and ion levels in their respective cellular compartments—early endosomes for NHE6, the Golgi for NHE7.  The researchers suspect that an increase in NHE7 would disrupt the pH in the Golgi compartment and that this, too, could lead to amyloidosis.

How big an effect might the SLC9A7 variant have on AD risk? Because X chromosome inactivation complicates the analyses, Belloy and colleagues came up with a statistical method to account for it. This model suggested that an active SLC9A7 risk variant could nudge up expression of the gene in brain tissue, but only by 16 to 44 percent. Though this seems small, the clinical relevance may be greater, Belloy said. “We think that in early life, you can tolerate a small difference in expression of this gene, but as you age, that becomes more of an issue and can contribute to a build-up of amyloid and tau pathology,” he said. The variant associated with AD in both women and men.

Also X inactivated in women is MTM1, a locus that just missed genome-wide statistical significance. In contrast, the four other loci that passed X chromosome-wide significance—NLGN4X, MID1, ZNF280C, and ADGRG4—appear to escape X inactivation. Therefore, they are likely to affect women more than men.

Bellenguez and colleagues analyzed data from 115,841 AD or AD-proxy cases and 613,671 controls that they obtained from the International Genomics of Alzheimer’s Project, European Alzheimer & Dementia Biobank, UKB, and FinnGen. First authors Julie Le Borgne and Lissette Gomez identified four loci that reached X chromosome-wide, though again not genome-wide, significance. Two fell in introns of genes that are X-inactivated, namely FRMPD4 and DMD. The former regulates dendritic spines and neurotransmission and variants in it cause X-linked intellectual disability. Variants in the adjacent gene MSL3, which is not subject to X-inactivation, cause neurodevelopmental delay (Piard et al., 2018; Basilicata et al., 2018).

Variants in DMD, which encodes dystrophin, cause Duchenne muscular dystrophy, which mostly affects boys, and about one-third of them also have cognitive impairment. In male mice, DMD mutations may trigger amyloidosis in the prefrontal cortex and hippocampus (Hayward et al., 2022). 

Functional effects for the other two loci are difficult to predict, the authors say, since they both are more than 300bp away from the nearest gene, namely NLGN4X and GRIA3. Dubal previously tied GRIA3 expression to cognitive resilience in women, but the locus Borgne and colleagues identified only associated with AD in men (Davis et al., 2021). 

AD Loci? Variants near the TBX22 and Haus7 genes reached the chromosome-wide significance threshold in an XWAS meta-analyses of pathologically confirmed AD. [Courtesy of Escott-Price et al., 2024]

Though their study was smaller, Escott-Price and her colleagues included data from 1,970 people who had had pathologically confirmed AD from 1,113 controls. First author Emily Simmonds analyzed datasets from three tissue bank cohorts: Brains for Dementia Research UK; a KRONOS/Tgen dataset derived from 21 National Alzheimer’s Coordinating Center brain banks and the Miami Brain Bank; and a combination of the Religious Orders Study/Memory and Aging Project, Mount Sinai Brain Bank, and Mayo Clinic Brain Bank. The analysis yielded 264,793 SNPs, of which two, at the TBX22 and Haus7 loci, reached chromosome-wide significance in meta-analysis of all three cohorts, while one, NXF5, passed muster in women only. The authors were intrigued by TBX22 and three other candidate genes, DDX53, IL1RAPL1, and SH3BGRL because all four turned up in separate analysis of at least two of the three cohorts.

Anomalies in three of these genes have previously been reported in various AD models, including elevated expression of DDX53, suppression of IL1RAPL1, and evidence of both in SH3BGRL. NXF5 deficiency has been linked to intellectual disabilities (Callaerts-Vegh et al., 2015). 

“Collectively, these studies highlight our emerging and high value for the X chromosome as a contributor to neural-related functions and as a source of sex difference,” Dubal said.

Both Belloy and Bellenguez suspect that variants in genes that escape inactivation help explain the sex differences in AD seen clinically. Women, for example, have less cognitive resilience to AD pathology, as determined by amyloid PET, than men. And yet, they have greater brain resilience to the effects of tangles than men (see Arenaza-Urquijo et al., 2024, for a review). 

Teasing out such effects with XWAS alone may be difficult. Other X chromosome-related factors may also play a role in AD, including epigenetic alterations of the X, genomic imprinting, and X-linked proteomic signatures, noted Rachel Buckley and Mabel Seto, Brigham & Women’s Hospital, Boston, in a JAMA Neurology editorial. “None of these components are effectively captured by XWAS,” they wrote.

Belloy agreed that these phenomena are grist for future analyses. “Our study will allow us to really start exploring how the X chromosome may be implicated in sex differences in Alzheimer’s disease,” he said. “This was a first step.”—Kristel Tjandra

Kristel Tjandra is a freelance writer in Springfield, Virginia.

Comments

    • User Profile Image Dena Dubal
      University of California, San Francisco
    • Posted:

    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 Dubal

  2. 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 Bellenguez

  3. After decades of the X chromosome remaining in the dark, it is wonderful now to have, in addition to ours, two additional Alzheimer’s disease XWAS papers see the light of day (Le Borgne et al., 2024; Simmonds et al., 2024). I believe this corroborates the timeliness of the research question to study the X chromosome in Alzheimer’s disease genetics, as well as the fact that our technologies and sample sizes have now advanced far enough to begin to tackle it.

    Across these three studies, there are differences in approaches, methods, phenotypes, and sample sizes, which in sum produced a set of suggestively associated loci (variants passing P-values <1e-5 in Belloy et al., corresponding to a typical suggestive threshold; P-values < ~2e-5 in Simmonds et al., corresponding to an FDR-correction for X chromosome SNPs; and P-values < 1.7e-6 in Le Borgne et al., corresponding to a Bonferroni correction for X chromosome SNPs) and one genome-wide significant locus (the conventional threshold of P-values < 5e-8) on SLC9A7 in Belloy et al. If the suggestive P-value < 1.7e-6 threshold from Le Borgne, which marked four loci in their work, was considered across all studies, this would retain three out of four common variant loci in Belloy et al. and one common variant locus in Simmonds et al., for a total of eight independent lead variants across seven loci.

    In trying to make sense of these signals, it is important to understand that power in XWAS is more challenging than in autosomal genome-wide association studies (GWAS). Power in genetic association studies relates to how much of the variance a variant can explain in a phenotype. Sidorenko et al., 2019, nicely illustrate that in men, due to hemizygosity (one X chromosome copy), there is half the power compared to the autosomes. In women, when there is random X chromosome inactivation (r-XCI), which is expected for ~70 percent of the X chromosome, the power is even further reduced, down to 1/4 compared to the autosomes. This emphasizes why one may be more lenient in paying attention to the suggestive signals on the X chromosome, as they may still be highly promising, while at the same time remaining mindful that those signals may harbor false positive associations.

    Another way to assess the potential relevance of a GWAS or XWAS association signal is to look for functional support at that locus. Typically, GWAS or XWAS require post hoc analyses to address this, and one of the most common approaches currently is to run genetic co-localization analyses with “QTL data.” These represent genetic association analyses with, e.g., expression levels of a given gene in a given tissue. By assessing whether the genetic signal for Alzheimer’s disease at a locus overlaps with the genetic signal for the expression of a gene in that locus, we get an initial insight into a potential causal relationship (genetic regulation of that gene’s expression may in turn affect risk for Alzheimer’s disease). In Belloy et al. this approach was implemented and supported all four common variant loci, including the prioritization of SLC9A7 at that locus. It would be interesting to see if the studies by Le Borgne et al. and Simmonds et al. could similarly identify functional support for their loci.

    Looping back to power, the studies by Belloy et al. and Le Borgne et al. are more similar in their approach and aim. The best way to compare these studies is to consider “effective sample sizes” (a more comparable measure that estimates sample size under a balanced sample design: 50/50 cases and controls). We calculated this while factoring in that datasets with proxy samples should have sample sizes divided by four to account for reduced power (Liu et al., 2016). This would indicate in Belloy et al. that the effective sample size was N=273 ,815, while in Le Borgne et al. it was N=235,757. As noted earlier, however, power on the X chromosome is further decreased relative to autosomes, notably in female samples. The study by Belloy et al. was able to leverage a large sample from the Million Veterans Program (MVP), which is primarily male-skewed when using the health registry phenotype subset (MVP-1). This likely contributed to an additional power gain in Belloy et al. relative to Le Borgne et al.

    A final factor to consider is the phenotypes used. In Belloy et al., there was a larger fraction of proxy cases relative to Le Borgne et al., which may raise concern about the validity of the associations and specificity to Alzheimer’s disease rather than dementia generally. However, sensitivity analyses in Belloy et al. confirmed that all associated loci had near-identical effect sizes even when proxy datasets were excluded. This is where the smaller study by Simmonds et al. provides a nice addition, in that it may identify loci that are more specifically associated with Alzheimer’s disease pathology. It can also be leveraged to verify the Alzheimer’s disease specificity of those identified in the studies by Belloy et al. and Le Borgne et al. The top variant at the SCL9A7 locus, under the random XCI model (where the effect size corresponds to half an active allele), in Belloy et al., indicated an odds ratio (OR) = 1.027. This same variant under the random XCI model, in Simmonds et al., indicated OR = 1.046, suggesting the association may be more pronounced with Alzheimer’s disease pathology confirmed individuals.

    Taken together, these three XWAS represent an exciting initial foray into the X chromosome in Alzheimer’s disease genetics and pave the work for new studies, including mapping endophenotypes and integration with multi-omics datasets to corroborate these newly associated loci and, ultimately, to identify novel drug targets.

    References:

    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.

    Simmonds E, Leonenko G, Yaman U, Bellou E, Myers A, Morgan K, Brookes K, Hardy J, Salih D, Escott-Price V. Chromosome X-wide association study in case control studies of pathologically confirmed Alzheimer's disease in a European population. Transl Psychiatry. 2024 Sep 4;14(1):358. PubMed.

    Sidorenko J, Kassam I, Kemper KE, Zeng J, Lloyd-Jones LR, Montgomery GW, Gibson G, Metspalu A, Esko T, Yang J, McRae AF, Visscher PM. The effect of X-linked dosage compensation on complex trait variation. Nat Commun. 2019 Jul 8;10(1):3009. PubMed.

    Liu JZ, Erlich Y, Pickrell JK. Case-control association mapping by proxy using family history of disease. Nat Genet. 2017 Mar;49(3):325-331. Epub 2017 Jan 16 PubMed.

    View all comments by Michael Belloy

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References

News Citations

  1. Could Juicing Up Trafficking Abolish ApoE4’s Alzheimer’s Risk?

Paper Citations

  1. Peeters SB, Posynick BJ, Brown CJ. Out of the Silence: Insights into How Genes Escape X-Chromosome Inactivation. Epigenomes. 2023 Nov 23;7(4) PubMed.
  2. Pohlkamp T, Xian X, Wong CH, Durakoglugil MS, Werthmann GC, Saido TC, Evers BM, White CL 3rd, Connor J, Hammer RE, Herz J. NHE6 depletion corrects ApoE4-mediated synaptic impairments and reduces amyloid plaque load. Elife. 2021 Oct 7;10 PubMed.
  3. Piard J, Hu JH, Campeau PM, Rzonca S, Van Esch H, Vincent E, Han M, Rossignol E, Castaneda J, Chelly J, Skinner C, Kalscheuer VM, Wang R, Lemyre E, Kosinska J, Stawinski P, Bal J, Hoffman DA, Schwartz CE, Van Maldergem L, Wang T, Worley PF. FRMPD4 mutations cause X-linked intellectual disability and disrupt dendritic spine morphogenesis. Hum Mol Genet. 2018 Feb 15;27(4):589-600. PubMed.
  4. Basilicata MF, Bruel AL, Semplicio G, Valsecchi CI, Aktaş T, Duffourd Y, Rumpf T, Morton J, Bache I, Szymanski WG, Gilissen C, Vanakker O, Õunap K, Mittler G, van der Burgt I, El Chehadeh S, Cho MT, Pfundt R, Tan TY, Kirchhoff M, Menten B, Vergult S, Lindstrom K, Reis A, Johnson DS, Fryer A, McKay V, DDD Study, Fisher RB, Thauvin-Robinet C, Francis D, Roscioli T, Pajusalu S, Radtke K, Ganesh J, Brunner HG, Wilson M, Faivre L, Kalscheuer VM, Thevenon J, Akhtar A. De novo mutations in MSL3 cause an X-linked syndrome marked by impaired histone H4 lysine 16 acetylation. Nat Genet. 2018 Oct;50(10):1442-1451. Epub 2018 Sep 17 PubMed.
  5. Hayward GC, Caceres D, Copeland EN, Baranowski BJ, Mohammad A, Whitley KC, Fajardo VA, MacPherson RE. Characterization of Alzheimer's disease-like neuropathology in Duchenne's muscular dystrophy using the DBA/2J mdx mouse model. FEBS Open Bio. 2022 Jan;12(1):154-162. Epub 2021 Nov 11 PubMed.
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  7. Callaerts-Vegh Z, Ahmed T, Vermaercke B, Marynen P, Balschun D, Froyen G, D'Hooge R. Nxf7 deficiency impairs social exploration and spatio-cognitive abilities as well as hippocampal synaptic plasticity in mice. Front Behav Neurosci. 2015;9:179. Epub 2015 Jul 10 PubMed.
  8. Arenaza-Urquijo EM, Boyle R, Casaletto K, Anstey KJ, Vila-Castelar C, Colverson A, Palpatzis E, Eissman JM, Kheng Siang Ng T, Raghavan S, Akinci M, Vonk JM, Machado LS, Zanwar PP, Shrestha HL, Wagner M, Tamburin S, Sohrabi HR, Loi S, Bartrés-Faz D, Dubal DB, Vemuri P, Okonkwo O, Hohman TJ, Ewers M, Buckley RF, Reserve, Resilience and Protective Factors Professional Interest Area, Sex and Gender Professional Interest area and the ADDRESS! Special Interest Group. Sex and gender differences in cognitive resilience to aging and Alzheimer's disease. Alzheimers Dement. 2024 Aug;20(8):5695-5719. Epub 2024 Jul 5 PubMed.

Further Reading

No Available Further Reading

Primary Papers

  1. Belloy ME, Le Guen Y, Stewart I, Williams K, Herz J, Sherva R, Zhang R, Merritt V, Panizzon MS, Hauger RL, Gaziano JM, Logue M, Napolioni V, Greicius MD. Role of the X Chromosome in Alzheimer Disease Genetics. JAMA Neurol. 2024 Oct 1;81(10):1032-1042. PubMed.
  2. 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.
  3. Simmonds E, Leonenko G, Yaman U, Bellou E, Myers A, Morgan K, Brookes K, Hardy J, Salih D, Escott-Price V. Chromosome X-wide association study in case control studies of pathologically confirmed Alzheimer's disease in a European population. Transl Psychiatry. 2024 Sep 4;14(1):358. PubMed.
  4. Buckley RF, Seto M. How Is the X Chromosome Involved in Alzheimer Disease?. JAMA Neurol. 2024 Oct 1;81(10):1028-1029. PubMed.

Follow-On Reading

Papers

  1. Le Borgne 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, Campos-Martin R, van der Lee S, Damotte V, de Rojas I, Palmal S, EADB, GR@ACE, DEGESCO, EADI, GERAD, DemGene, FinnGen, ADGC, CHARGE, Lipton R, Reiman E, McKee A, De Jager P, Bush W, Small S, Levey A, Saykin A, Foroud T, Albert M, Hyman B, Petersen R, Younkin S, Sano M, Wisniewski T, Vassar R, Schneider J, Henderson V, Roberson E, DeCarli C, LaFerla F, Brewer J, Swerdlow R, Van Eldik L, Hamilton-Nelson K, Paulson H, Naj A, Lopez O, Chui H, Crane P, Grabowski T, Kukull W, Asthana S, Craft S, Strittmatter S, Cruchaga C, Leverenz J, Goate A, Kamboh MI, George-Hyslop PS, Valladares O, Kuzma A, Cantwell L, Riemenschneider M, Morris J, Slifer S, Dalmasso C, Castillo A, Küçükali F, Peters O, Schneider A, Dichgans M, Rujescu D, Scherbaum N, Deckert J, Riedel-Heller S, Hausner L, Molina-Porcel L, Düzel E, Grimmer T, Wiltfang J, Heilmann-Heimbach S, Moebus S, Tegos T, Scarmeas N, Dols-Icardo O, Moreno F, Pérez-Tur J, Bullido MJ, Pastor P, Sánchez-Valle R, Álvarez V, Boada M, García-González P, Puerta R, Mir P, Real LM, Piñol-Ripoll G, García-Alberca JM, Royo JL, Rodriguez-Rodriguez E, Soininen H, de Mendonça A, Mehrabian S, Traykov L, Hort J, Vyhnalek M, Thomassen JQ, Pijnenburg YA, Holstege H, van Swieten J, Ramakers I, Verhey F, Scheltens P, Graff C, Papenberg G, Giedraitis V, Boland A, Deleuze JF, Nicolas G, Dufouil C, Pasquier F, Hanon O, Debette S, Grünblatt E, Popp J, Ghidoni R, Galimberti D, Arosio B, Mecocci P, Solfrizzi V, Parnetti L, Squassina A, Tremolizzo L, Borroni B, Nacmias B, Spallazzi M, Seripa D, Rainero I, Daniele A, Bossù P, Masullo C, Rossi G, Jessen F, Fernandez V, Kehoe PG, Frikke-Schmidt R, Tsolaki M, Sánchez-Juan P, Sleegers K, Ingelsson M, Haines J, Farrer L, Mayeux R, Wang LS, Sims R, DeStefano A, Schellenberg GD, Seshadri S, Amouyel P, Williams J, van der Flier W, Ramirez A, Pericak-Vance M, Andreassen OA, Van Duijn C, Hiltunen M, Ruiz A, Dupuis J, Martin E, Lambert JC, Kunkle B, Bellenguez C. X-chromosome-wide association study for Alzheimer's disease. Mol Psychiatry. 2024 Dec 4; Epub 2024 Dec 4 PubMed.

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