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Find studies

Showing 501–525 of 847 studies in Risk genes beyond APOE (page 21 of 34) · 27,380 in the whole library · How the 0–100 score works

Browse by subject, author or institution

Each number is how many studies that link shows, with your other filters kept.

What “Risk genes beyond APOE” covers

Risk genes beyond APOE — Genome-wide studies and individual genes other than APOE that shift Alzheimer's risk.

A note on reading research. One study is rarely the final word.

We try to note the size of a study, whether it was in humans or animals, and how early-stage the finding is. If a summary here doesn't make that clear, treat it with extra caution and check the original source.

The deposition of amyloid in senile plaques and along the walls of the cerebral vasculature is a characteristic feature of Alzheimer disease. 4 key findings →

Evidence: low

Abnormal activation of calpain is implicated in synaptic dysfunction and participates in neuronal death in Alzheimer disease (AD) and other neurological disorders. 4 key findings →

Evidence: low

Whereas neurotoxic Aβ is derived from amyloid precursor protein (APP) by β- and γ-secretase cleavage, APP processing along the non-amyloidogenic pathway results in the secretion of the large neurotrophic ectodomain APPsα. 2 key findings →

Evidence: low

The ER protein CANX (calnexin)-mediated autophagy protects against alzheimer disease

✓ Peer-reviewed alzhub usefulness score 42 out of 100. Autophagy 2025-01-15

Although the relationship between macroautophagy/autophagy and Alzheimer disease (AD) is widely studied, the underlying mechanisms are poorly understood, especially the regulatory role of the initiation signaling of autophagy on AD. 2 key findings →

Evidence: low

Familial Alzheimer's disease (FAD) is caused by dominant missense mutations in amyloid precursor protein (APP) and presenilin-1 (PSEN1), the catalytic component of γ-secretase that generates amyloid β-peptides (Aβ) from the APP C-terminal fragment C99. 3 key findings →

Evidence: low

IMAGING OF THE BONE ARCHITECTURE IN THE CONTEXT OF ALZHEIMER DISEASE

✓ Peer-reviewed alzhub usefulness score 42 out of 100. Osteoarthritis Imaging 2026-01-01

Female Psen1 mutation(L166P) mice were found to have reductions in whole-body mineral density (BMD) and bone mineral content as early as one month and a sustained bone phenotype with age with loss in cortical and trabecular properties compared to age-and gendermatched wildtype control mice, whereas male mice did not (Fig.1A-C). 5 key findings →

Evidence: low

The extracellular accumulation of amyloid-beta (Abeta) in neuritic plaques is one of the characteristic hallmarks of Alzheimer's disease (AD), a progressive dementing neurodegenerative disorder of the elderly. 4 key findings →

Evidence: low

Prior work has shown that iron interacts with hyperphosphorylated tau, which contributes to the formation of neurofibrillary tangles (NFTs) in Alzheimer's disease (AD), whereas iron chelator desferrioxamine (DFO) slows down the clinical progression of the cognitive decline associated with this disease. 4 key findings →

Evidence: low

A change of the prion protein conformation results in a class of neurodegenerative diseases called the transmissible spongiform encephalopathies (like mad cow and Creutzfeld-Jakob diseases). 4 key findings →

Evidence: low

Active immunization with the human amyloid peptide (Abeta42) or passive immunization with anti-Abeta42 antibodies protects mice that express a mutant human amyloid precursor protein (APP) transgene from cerebral amyloid deposits. 4 key findings →

Evidence: low

The amyloid-beta (Aβ) peptide is the derivative of amyloid precursor protein (APP) generated through sequential proteolytic processing by β- and γ-secretases. 4 key findings →

Evidence: low

beta-Amyloid peptides (Abeta) that form the senile plaques of Alzheimer disease consist mainly of 40- and 42-amino acid (Abeta 40 and Abeta 42) peptides generated from the cleavage of the amyloid precursor protein (APP). 4 key findings →

Evidence: low

Retinal amyloid peptides and complement factor H in transgenic models of Alzheimer's disease

✓ Peer-reviewed alzhub usefulness score 41 out of 100. Neuroreport 2011-08-01

Murine transgenic models of Alzheimer's disease (Tg-AD) have been useful to analyze the contribution of β-amyloid precursor protein (βAPP), Aβ42 peptide deposition, and the proinflammatory mechanisms that characterize Alzheimer-type neuropathology. 4 key findings →

Evidence: low

Neurodegenerative processes in Alzheimer disease (AD) are thought to be driven in part by the deposition of amyloid beta (A beta), a 39- to 43-amino acid peptide product resulting from an alternative cleavage of amyloid precursor protein. 4 key findings →

Evidence: low

Pharmacological modulation of the GABA(A) receptor has gained increasing attention as a potential treatment for central processes affected in Alzheimer disease (AD), including neuronal survival and cognition. 4 key findings →

Evidence: low

Alzheimer disease (AD) brain is characterized by extracellular plaques of amyloid β (Aβ) peptide with reactive microglia. 4 key findings →

Evidence: low

We have recently identified a new form of post-translational regulation of BACE1 (beta-site amyloid precursor protein (APP)-cleaving enzyme 1), a membrane protein that acts as the rate-limiting enzyme in the generation of the Alzheimer disease amyloid beta-peptide (Abeta). 4 key findings →

Evidence: low

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Where “Free full text” comes from

Free full text links and the Full text may need a subscription label come from Unpaywall, Europe PMC and OpenAlex records of free copies, checked 10 Oct 2026. A study with neither is unknown, not paywalled. Show only studies that are free to read

How the 0–100 score works — and why some entries are capped

This is alzhub's own score. It is not an official metric, not an impact factor, and no journal, publisher or ranking body endorses it. We built it so that a reader who is not a scientist can tell a landmark trial from a conference abstract without having to already know the difference. Every point comes from one of 20 components, all of them printed on the study itself, so you can disagree with our arithmetic rather than having to trust the total.

  • Journal tier up to 10 pts
  • Journal's citation record up to 4 pts
  • Study design up to 12 pts
  • Strength of evidence up to 5 pts
  • Peer-review validation up to 10 pts
  • How recent up to 5 pts
  • Sample size up to 4 pts
  • Effect reported up to 3 pts
  • Studied in people up to 3 pts
  • Randomised / blinded up to 2 pts
  • Times cited up to 7 pts
  • Citations per year up to 5 pts
  • Impact for its field and year up to 6 pts
  • Cited by studies here up to 6 pts
  • Still being cited up to 4 pts
  • Senior author's track record up to 4 pts
  • Institution's track record up to 3 pts
  • Multi-centre collaboration up to 3 pts
  • Indexed in PubMed up to 2 pts
  • Free to read up to 2 pts

Journals are placed in ordered tiers, never given a numeric impact factor — we could not verify current impact factors from a source we control, and an invented one would be worse than none. Tier 1 is the top-tier general journals (NEJM, The Lancet, JAMA, Nature, Science, Nature Medicine); tier 2 is the leading specialty journals; tier 3 is every other peer-reviewed journal. A separate part scores how much the journal's own papers are cited, which tells the tier-3 journals apart.

Two rules we don't bend. First, we never fill in a missing value: if a record does not state a sample size or a design, that component scores zero, and if we simply have no data for a part, such as a citation count, that part is left out and the study is scored on the parts we could check. The study card says which. Second, anything that is not a peer-reviewed article is capped at 16/100 and carries a warning chip — so a conference abstract or a company press release can never outrank a peer-reviewed paper, no matter how good it looks.

We rank a rigorous null result — a good trial showing that something does not work — above an early positive finding. Someone deciding whether to buy a supplement is served by that, and the rigour is already counted by the design and journal components.

The score is computed from the published data alone and is reproducible: the same file always yields the same numbers.

See the whole rubric drawn out → — four charts covering all 27,380 studies: how the scores are spread and where the cap bites, which of the 20 components the library is strong and weak on, which subjects rest on stronger evidence, and what kinds of study each subject is actually built from.

What this library is — and isn't

This is a large sample of the Alzheimer's literature, not an exhaustive index of it. It holds 27,380 records, built mostly from automated pulls of Europe PMC (60.6% of the library) and OpenAlex (18.6%), plus smaller pulls from PubMed, Crossref and medRxiv. If a study, a drug, or a finding isn't here, that is not evidence it doesn't exist in the literature — it may simply not have been pulled in yet.

1,032 records (3.8% of the library) are not peer-reviewed — 962 of those are preprints posted before any journal review, and the rest are conference abstracts, regulatory notices and reports. Every study card on this page states its status plainly, and the score above is capped for anything that isn't a peer-reviewed article.

See the full, machine-readable breakdown of this library's coverage →

Newest studies, as a dated timeline →    Atom feed