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Clinical, genetic, and phenotypic studies of dementia provide some insights of the observed progressive neurodegenerative processes, however, the mechanisms underlying AD onset remain enigmatic.<\/jats:p><\/jats:sec><jats:sec><jats:title>Aims<\/jats:title><jats:p>This paper examines late\u2010onset dementia\u2010related cognitive impairment utilizing neuroimaging\u2010genetics biomarker associations.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and Methods<\/jats:title><jats:p>The participants, ages 65\u201385, included 266 healthy controls (HC), 572 volunteers with mild cognitive impairment (MCI), and 188 Alzheimer's disease (AD) patients. Genotype dosage data for AD\u2010associated single nucleotide polymorphisms (SNPs) were extracted from the imputed ADNI genetics archive using sample\u2010major additive coding. Such 29 SNPs were selected, representing a subset of independent SNPs reported to be highly associated with AD in a recent AD meta\u2010GWAS study by Jansen and colleagues<jats:italic>.<\/jats:italic><\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We identified the significant correlations between the 29 genomic markers (GMs) and the 200 neuroimaging markers (NIMs). The odds ratios and relative risks for AD and MCI (relative to HC) were predicted using multinomial linear models.<\/jats:p><\/jats:sec><jats:sec><jats:title>Discussion<\/jats:title><jats:p>In the HC and MCI cohorts, mainly cortical thickness measures were associated with GMs, whereas the AD cohort exhibited different GM\u2010NIM relations. Network patterns within the HC and AD groups were distinct in cortical thickness, volume, and proportion of White to Gray Matter (pct), but not in the MCI cohort. Multinomial linear models of clinical diagnosis showed precisely the specific NIMs and GMs that were most impactful in discriminating between AD and HC, and between MCI and HC.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>This study suggests that advanced analytics provide mechanisms for exploring the interrelations between morphometric indicators and GMs. The findings may facilitate further clinical investigations of phenotypic associations that support deep systematic understanding of AD pathogenesis.<\/jats:p><\/jats:sec>","DOI":"10.1111\/cns.14073","type":"journal-article","created":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T07:10:50Z","timestamp":1672211450000},"page":"1034-1048","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Brain structure and allelic associations in Alzheimer's 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