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Alzheimer’s Disease Risk Genes and Mechanisms of Disease Pathogenesis
Open accessAbstract
We review the genetic risk factors for late-onset Alzheimer's disease (AD) and their role in AD pathogenesis. More recent advances in understanding of the human genome-technologic advances in methods to analyze millions of polymorphisms in thousands of subjects-have revealed new genes associated with AD risk, including ABCA7, BIN1, CASS4, CD33, CD2AP, CELF1, CLU, CR1, DSG2, EPHA1, FERMT2, HLA-DRB5-DBR1, INPP5D, MS4A, MEF2C, NME8, PICALM, PTK2B, SLC24H4-RIN3, SORL1, and ZCWPW1. Emerging technologies to analyze the entire genome in large data sets have also revealed coding variants that increase AD risk: PLD3 and TREM2. We review the relationship between these AD risk genes and the cellular and neuropathologic features of AD. Understanding the mechanisms underlying the association of these genes with risk for disease will provide the most meaningful targets for therapeutic development to date.
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“PSEN1 is the catalytical component of 𝛄 -secretase (304).”
From Blood-Brain Barrier: From Physiology to Disease and Back (2019) · cites this paper as [304]
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“To date, 228 PSEN1 mutations have been identified causing ADAD (49, 303, 304, 440, 566, 580).”
From Blood-Brain Barrier: From Physiology to Disease and Back (2019) · cites this paper as [304]
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“Some PSEN1 mutations lead to very early onset ADAD ( < 35 yr of age) (177, 304).”
From Blood-Brain Barrier: From Physiology to Disease and Back (2019) · cites this paper as [304]
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“TREM2 loss‐of‐function impairs microglial protective functions and worsens neuronal dystrophy. 9 , 37 , 38 , 41 , 42 , 61”
From PLCG2 modulates TREM2 expression and signaling in response to Alzheimer's disease pathology (2025) · cites this paper as [9]
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“approximately 40% of the susceptibility genes identified in genetic studies of LOAD are immune- and microglia-related, suggesting that microglia are involved in modulating AD pathology [8].”
From PLCG2 is associated with the inflammatory response and is induced by amyloid plaques in Alzheimer’s disease (2022) · cites this paper as [8]
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“In addition, genome-wide association studies have identified associations between inflammation- and immune-related variants in genes (such as a missense mutation in the gene encoding for TREM2, a receptor expressed on microglia) and increased AD risk [36].”
From Cerebrospinal fluid levels of the neurotrophic factor neuroleukin are increased in early Alzheimer’s disease, but not in cerebral amyloid angiopathy (2021) · cites this paper as [36]
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“Most notably, these genetic studies implicate central roles for the innate immune system, with many AD risk genes being primarily expressed in microglia (Efthymiou and Goate, 2017; Karch and Goate, 2015; Lopes et al., 2022).”
From Alzheimer’s genetic risk factor CASS4 controls microglial focal adhesion biology and amyloidosis (2026) · cites this paper as Karch and Goate, 2015
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“among the top risk genes for sporadic AD, APOE, TREM2, APOJ, PICALM, ABCA7, and SORL1 are all directly involved in lipid trafficking or metabolism (Karch and Goate, 2015).”
From ApoE4 Impairs Neuron-Astrocyte Coupling of Fatty Acid Metabolism (2021) · cites this paper as Karch and Goate, 2015
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“More than half of the reported genetic risk factors of AD are related to microglia-mediated immune response and cholesterol metabolism (Karch and Goate, 2015).”
From Cholesterol 25-hydroxylase mediates neuroinflammation and neurodegeneration in a mouse model of tauopathy (2024) · cites this paper as Karch and Goate, 2015
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“Disruption of retromer-dependent endosomal trafficking is considered pathogenic in late-onset Alzheimer’s disease (AD).”
From The neuronal retromer can regulate both neuronal and microglial phenotypes of Alzheimer's disease (2022) · cites this paper as Karch and Goate, 2015
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“the main genetic risk factor in SAD is the APOE gene [91,92,93,94].”
From Alzheimer's Disease: Treatment Strategies and Their Limitations. (2022) · cites this paper as [94]
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“Autosomal-dominant AD (ADAD) is an inherited form of AD caused by mutations in amyloid precursor protein ( APP ) and presenilin-1 and 2 ( PSEN1; PSEN2 ) genes (49, 177, 303, 304, 580).”
From Blood-Brain Barrier: From Physiology to Disease and Back (2019) · cites this paper as [304]
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“Genetic studies have identified numerous AD risk variants in immune‐ and microglial‐associated genes, highlighting the importance of microglia function in disease progression. 3 , 4 , 5 , 6 , 7”
From Alzheimer's disease–associated PLCG2 variants alter microglial state and function in human induced pluripotent stem cell–derived microglia‐like cells (2025) · cites this paper as [5]
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“Moreover, HLA‐DRB polymorphisms are associated with increased risk of AD 2 , 19 , 20”
From The P522R protective variant of PLCG2 promotes the expression of antigen presentation genes by human microglia in an Alzheimer's disease mouse model (2022) · cites this paper as [2]
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“Identifying functional variants, such as the variants in APP, APOE, PLD3, and TREM2 provide key insights into disease mechanisms [14, 15].”
From Linkage, whole genome sequence, and biological data implicate variants in RAB10 in Alzheimer’s disease resilience (2017) · cites this paper as [15]
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“In recent years, genetic and functional studies have highlighted the endo-lysosomal network as a key biological pathway central to AD pathogenesis [3–5].”
From Retromer Stabilization Improves Cognitive Function and Synaptic Plasticity in a Mouse Model of Down Syndrome (2023) · cites this paper as [3]
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“Inpp5d is expressed predominantly in microglia but its function in brain is poorly understood.”
From Loss of Inpp5d has disease‐relevant and sex‐specific effects on glial transcriptomes (2024) · cites this paper as [16]
Experimental — accuracy not yet measuredIn the citing paper
“Likewise, genome-wide association studies (GWAS) have identified several single-nucleotide polymorphisms (SNPs) in immune genes as independent risk factors for LOAD [52–55], directly implicating microglia-mediated mechanisms in sporadic AD progression.”
From Systems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau (2021) · cites this paper as [55]
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Citations
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Metadata
- Authors
- Karch, C. M., & Goate, A. M.
- Affiliations
- Washington University in St. Louis (US)
- Corresponding author
- Goate, Alison M.
- Venue
- Biological Psychiatry
- Publisher
- Elsevier BV
- Published
- 2015-01
- Volume
- 77
- Issue
- 1
- Pages
- 43-51
- ISSN
- 0006-3223 (ISSN-L)
- PMC
- PMC4234692
- OpenAlex
- W1999794509
- Cited by
- 1,357
- References
- 149
- Citations by year
- 2026: 80 · 2025: 136 · 2024: 130 · 2023: 132 · 2022: 151 · 2021: 153 · 2020: 146 · 2019: 117 · 2018: 94 · 2017: 94 · 2016: 74 · 2015: 44
- FWCI
- 8.50
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Biological Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Wellcome Trust (503147, G0801418)
- National Institute on Aging (K01AG046374, R01AG035083, P50AG005681, U01AG032438)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- Alzheimer's disease, late-onset Alzheimer's disease, genetic risk factors, susceptibility genes, Alzheimer's disease pathogenesis, single nucleotide polymorphisms, ABCA7, BIN1, SORL1, TREM2, PLD3, CD33, PICALM, clusterin, neuropathology, therapeutic target
- MeSH terms
- Alzheimer Disease, Cholesterol, Endocytosis, Humans, Phenotype, Risk Factors, Amyloid beta-Protein Precursor, Genetic Predisposition to Disease, Presenilin-1, Presenilin-2, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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