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Find studies

Showing 1–24 of 24 studies with an author at Merck & Co., Inc., Rahway, NJ, USA (United States) (US) · 27,780 in the whole library · How the 0–100 score works

Download bibliography of these 24 studies, in this order: BibTeX (.bib) · RIS (.ris)

Browse by subject, author or institution

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

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.

Randomized Trial of Verubecestat for Mild-to-Moderate Alzheimer's Disease

✓ Peer-reviewed alzhub usefulness score 82 out of 100. The New England journal of medicine 2018-05-01

Verubecestat did not reduce cognitive or functional decline in patients with mild-to-moderate Alzheimer's disease and was associated with treatment-related adverse events. 3 key findings →

Participants: 1,958 Evidence: high

Inflammatory mechanisms have been implicated in Alzheimer's disease (AD) and might be mediated via the COX-2 enzyme. 3 key findings →

Participants: 725 Evidence: high

Memantine, an N-methyl-D-aspartate receptor antagonist, is approved in the United States and Europe for the treatment of moderate to severe Alzheimer disease (AD) and has also been investigated in patients with mild to moderate AD. 3 key findings →

Evidence: high

Integrated Systems Approach Identifies Genetic Nodes and Networks in Late-Onset Alzheimer’s Disease

✓ Peer-reviewed alzhub usefulness score 59 out of 100. Cell 2013-04-01

The study constructed gene-regulatory networks in postmortem brain tissues from late-onset Alzheimer's disease patients and nondemented subjects to characterize associated molecular systems. 3 key findings →

A lack of understanding of the causes of attrition in longitudinal studies of older adults may lead to higher attrition rates and bias longitudinal study results. 4 key findings →

Design: longitudinal study Participants: 30,433 Evidence: moderate

After adjusting for sociodemographics, comorbidities, and potential caregiving network, those with normal cognition received an average of 4.6 hours per week of informal care. 4 key findings →

Participants: 7,443 Evidence: low

The Alzheimer's Disease Neuroimaging Initiative (ADNI) beginning in October 2004, is a 6-year research project that studies changes of cognition, function, brain structure and function, and biomarkers in elderly controls, subjects with mild cognitive impairment, and subjects with Alzheimer's disease (AD). 2 key findings →

Evidence: low

Here, we review progress by the Penn Biomarker Core in the Alzheimer's Disease Neuroimaging Initiative (ADNI) toward developing a pathological cerebrospinal fluid (CSF) and plasma biomarker signature for mild Alzheimer's disease (AD) as well as a biomarker profile that predicts conversion of mild cognitive impairment (MCI) and/or normal control subjects to AD. 2 key findings →

Evidence: low

The β-site APP cleaving enzymes 1 and 2 (BACE1 and BACE2) were initially identified as transmembrane aspartyl proteases cleaving the amyloid precursor protein (APP). 4 key findings →

Evidence: low

Pathologic TAR-DNA-binding protein 43 (TDP-43) is a disease protein in frontotemporal lobar degeneration with ubiquitin-positive inclusions (FTLD-U) and amyotrophic lateral sclerosis. 4 key findings →

Evidence: low

TAR DNA binding protein-43 (TDP-43) is found in ubiquitinated inclusions (UBIs) in some frontotemporal dementias (FTD-U). 4 key findings →

Evidence: low

Apolipoprotein (apo) E4 is the major genetic risk factor for late-onset Alzheimer disease (AD). 4 key findings →

Evidence: low

Inclusion body myopathy associated with Paget's disease of bone and frontotemporal dementia (IBMPFD) is a dominantly inherited degenerative disorder caused by mutations in the valosin-containing protein (VCP7) gene. 4 key findings →

Evidence: low

Apolipoprotein (apo) E4 is the major genetic risk factor for Alzheimer disease (AD) and likely contributes to neuropathology through various pathways. 4 key findings →

Evidence: low

Predicting dementia with routine care EMR data

✓ Peer-reviewed alzhub usefulness score 44 out of 100. Artificial intelligence in medicine 2019-12-05

Our aim is to develop a machine learning (ML) model that can predict dementia in a general patient population from multiple health care institutions one year and three years prior to the onset of the disease without any additional monitoring or screening. 1 key finding →

Evidence: low

These data provide potential insights into the biology of CSF in AD and MCI progression and provide a novel tool for AD researchers and clinicians working to improve diagnostic accuracy, evaluation of treatment efficacy, and early diagnosis. 3 key findings →

Evidence: low

A novel pathway for amyloid precursor protein processing

✓ Peer-reviewed alzhub usefulness score 38 out of 100. Neurobiology of aging 2009-07-14

Amyloid precursor protein (APP) can be proteolytically processed along two pathways, the amyloidogenic that leads to the formation of the 40-42 amino acid long Alzheimer-associated amyloid β (Aβ) peptide and the non-amyloidogenic in which APP is cut in the middle of the Aβ domain thus precluding Aβ formation. 4 key findings →

Evidence: low

Leveraging real-world data to better understand health care utilization patterns prior to and after incident AD diagnosis may help inform the clinical management of the disease. 1 key finding →

Evidence: moderate

Real-world, administrative claims data is uniquely suited to help characterize the journey of Alzheimer's disease (AD) patients from the onset of disease symptoms through diagnosis and beyond. 3 key findings →

Evidence: moderate

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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 27,780 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 27,780 records, built mostly from automated pulls of Europe PMC (61.1% of the library) and OpenAlex (18.3%), 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.

1,034 records (3.7% 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 →

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