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An international study combining genetic data from nearly 2.8 million people identified 127 Alzheimer’s-associated genetic loci, including 48 not previously reported. The researchers also found that one method of estimating genetic heritability may undercount the contribution of common variants, though the study does not establish a revised overall heritability figure or prove that its proposed drug targets will work.
An international research team has identified 127 genetic loci associated with Alzheimer’s disease, including 48 not previously reported, in an analysis drawing on data from nearly 2.8 million people. The study, published in Nature, also suggests that a widely used method may have underestimated the contribution of common genetic variants to Alzheimer’s risk, although it does not provide a new overall heritability estimate that replaces earlier figures.
According to the study’s report in Nature, the researchers combined genetic summary data from 30 cohorts. The dataset included 109,479 people diagnosed with Alzheimer’s, 74,141 proxy cases, 2,131,799 controls and 499,708 proxy controls. Proxy cases were people whose mother or father was reported to have Alzheimer’s or dementia; they were not participants diagnosed with the disease themselves. The study’s reported effective sample size was 416,493.
The paper reports that the multi-ancestry analysis identified 118 significant loci, with nine more found in a European-ancestry-only analysis. Researchers also linked the genetic findings to biological pathways involving lipid binding, immune activation, amyloid processing and cell adhesion. Genes associated with microglia—the brain’s immune cells—showed enrichment for Alzheimer’s genetic associations. Some neuronal findings were weaker after adjustment for differences in gene expression across cell types.
Among genes prioritized at newly identified loci, the team highlighted RRM2B, SYK, KEAP1, CACNA1S and AXL as potential drug targets. These were candidates from genetic and biological analyses, not treatments tested in this study. The authors noted prior experimental work reporting promising findings for some targets, while interventions involving CACNA1S and AXL had not improved outcomes in cited human and animal studies.
What the Genetic Findings Add
The findings could help researchers build a fuller account of the biological processes associated with Alzheimer’s, rather than focusing only on a limited set of known risk regions. The study’s analyses link microglial immune activity and neuronal function to areas for follow-up research, including how inherited variation relates to changes in brain cells over time.
The study also bears on estimates of inherited risk. As the authors note, earlier twin studies have put Alzheimer’s susceptibility heritability at 60% to 80%, while estimates based on common single-nucleotide polymorphisms suggested those variants accounted for about 5% of disease liability. The new analysis raises a methodological concern: estimates can differ depending on how genetic data are analyzed. That matters for interpreting risk studies and for the development of genetic prediction tools, but it does not mean that an individual’s risk can be precisely predicted from these results.
The potential drug targets may guide laboratory work, but they are not evidence that medicines acting on them will prevent or treat Alzheimer’s. The study’s value at this stage is in identifying genetic associations and hypotheses for further testing.
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How Earlier Estimates Were Made
Alzheimer’s disease is the most common form of dementia. The study’s authors note that earlier genome-wide association studies had identified about 80 risk loci, while genetic association research has sought to map which inherited differences are linked to the disease and which biological mechanisms may connect them.
As described in the Nature paper, the team analyzed groups by ancestry and combined results across cohorts. About 91% of the effective sample came from people of European ancestry. The researchers used SBayesRC to estimate heritability from common genetic variants and compared its results with estimates from linkage disequilibrium score regression. They also ran simulations using UK Biobank data to examine differences between methods.
The study’s ancestry groups included European, African, East Asian, admixed American and South Asian participants. The authors reported that results were less precise in groups with smaller samples. This imbalance matters when considering how well the findings and genetic risk scores may apply across populations.
Limits of the Evidence
The results do not settle how much of Alzheimer’s susceptibility is genetic. The study compares heritability methods, but the reported findings do not establish a single revised percentage that can be applied to the population. Methodological estimates are not the same as an individual risk forecast, and the researchers’ genetic associations do not establish that particular variants directly cause disease.
There are also limits to the population data. The study reports that European-ancestry participants made up most of the effective sample, and that estimates for groups with smaller samples were less precise. It included proxy cases based on a parent’s reported diagnosis or dementia, as well as cases identified through clinical diagnoses or health records; some cohorts used unspecified dementia codes. Those features affect how precisely Alzheimer’s cases can be distinguished across the combined dataset.
The paper’s cell-type analyses also require care in interpretation. The microglial association remained significant after adjustment for average expression differences, while neuronal associations became only nominally significant. The study cannot determine whether the observed neuronal expression patterns contribute to Alzheimer’s or arise as a consequence of neurodegeneration. No candidate target was validated as a treatment in this analysis.
Validation Across Populations and Targets
Further research will need to test whether the newly identified loci and prioritized genes hold up in independent datasets, particularly in populations underrepresented in the current analysis. Larger samples across ancestry groups could make those estimates more precise and help evaluate whether genetic prediction tools perform consistently across populations.
Researchers can also investigate the proposed pathways and targets in experimental studies and, where evidence supports it, clinical research. The current report does not announce a treatment trial or a change to Alzheimer’s care. For now, the next step is replication and biological validation—including clarifying the role of microglia and whether neuronal expression changes are causes, consequences or both.
Key Questions
What did the study find?
Researchers identified 127 Alzheimer’s-associated genetic loci, including 48 not previously reported, and found evidence that a heritability method may underestimate the contribution of common variants, according to the study published in Nature.
Does this mean Alzheimer’s is more than 60% genetic?
No new overall percentage is established in the study findings. Earlier twin studies estimated heritability at 60% to 80%, while estimates for common variants have differed by method. Heritability describes variation in a population; it does not predict a particular person’s outcome.
Did the study test new Alzheimer’s medicines?
No. The Nature study identified genes and pathways that may merit further research. The proposed targets, including SYK and AXL, were not tested as treatments in this study.
Do the results apply equally across ancestry groups?
That is not yet clear. The study included several ancestry groups, but about 91% of its effective sample was European ancestry, and the researchers said results were less precise in groups with smaller samples.
Source: news-medical.net
