Alisa K Manning
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Explore the profile of Alisa K Manning including associated specialties, affiliations and a list of published articles.
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110
Citations
8096
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Recent Articles
1.
Sevilla-Gonzalez M, Smith K, Wang N, Jensen A, Litkowski E, Kim H, et al.
Nat Commun
. 2025 Mar;
16(1):2569.
PMID: 40089507
Elevated fasting insulin levels (FI), indicative of altered insulin secretion and sensitivity, may precede type 2 diabetes (T2D) and cardiovascular disease onset. In this study, we group FI-associated genetic variants...
2.
Westerman K, Patel C, Meigs J, Chasman D, Manning A
Genes Nutr
. 2025 Mar;
20(1):3.
PMID: 40038624
Discovery and translation of gene-environment interactions (GxEs) influencing clinical outcomes is limited by low statistical power and poor mechanistic understanding. Molecular omics data may help address these limitations, but their...
3.
Li X, Chen H, Selvaraj M, Van Buren E, Zhou H, Wang Y, et al.
Nat Comput Sci
. 2025 Feb;
5(2):125-143.
PMID: 39920506
Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in...
4.
Wilechansky R, Challa P, Han X, Hua X, Manning A, Corey K, et al.
Cancer Prev Res (Phila)
. 2025 Feb;
PMID: 39916630
Despite increasing incidence of hepatocellular carcinoma (HCC) in vulnerable populations, accurate early detection tools are lacking. We aimed to investigate the associations between pre-diagnostic plasma metabolites and incident HCC in...
5.
Luckett A, Oram R, Deutsch A, Ortega H, Fraser D, Ashok K, et al.
medRxiv
. 2025 Jan;
PMID: 39867414
Type 1 diabetes (T1D) polygenic risk scores (PRS) are effective tools for discriminating T1D from other diabetes types and predicting T1D risk, with applications in screening and intervention trials. A...
6.
Westerman K, Kilpelainen T, Sevilla-Gonzalez M, Connelly M, Wood A, Tsai M, et al.
Genet Epidemiol
. 2025 Jan;
49(1):e22607.
PMID: 39764704
Large-scale gene-environment interaction (GxE) discovery efforts often involve analytical compromises for the sake of data harmonization and statistical power. Refinement of exposures, covariates, outcomes, and population subsets may be helpful...
7.
Szczerbinski L, Mandla R, Schroeder P, Porneala B, Li J, Florez J, et al.
Sci Rep
. 2024 Nov;
14(1):26895.
PMID: 39505999
The All of Us Research Program (AoU) is an initiative designed to gather a comprehensive and diverse dataset from at least one million individuals across the USA. This longitudinal cohort...
8.
Huerta-Chagoya A, Schroeder P, Mandla R, Li J, Morris L, Vora M, et al.
Nat Genet
. 2024 Oct;
56(11):2576.
PMID: 39438755
No abstract available.
9.
Huerta-Chagoya A, Schroeder P, Mandla R, Li J, Morris L, Vora M, et al.
Nat Genet
. 2024 Oct;
56(11):2370-2379.
PMID: 39379762
Type 2 diabetes (T2D) genome-wide association studies (GWASs) often overlook rare variants as a result of previous imputation panels' limitations and scarce whole-genome sequencing (WGS) data. We used TOPMed imputation...
10.
Westerman K, Patel C, Meigs J, Chasman D, Manning A
medRxiv
. 2024 Sep;
PMID: 39314967
Discovery and translation of gene-environment interactions (GxEs) influencing clinical outcomes is limited by low statistical power and poor mechanistic understanding. Molecular omics data may help address these limitations, but their...