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Lynn M. Almli

Researcher at Emory University

Publications -  49
Citations -  3643

Lynn M. Almli is an academic researcher from Emory University. The author has contributed to research in topics: Genome-wide association study & DNA methylation. The author has an hindex of 28, co-authored 44 publications receiving 2834 citations.

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Largest GWAS of PTSD (N=20 070) yields genetic overlap with schizophrenia and sex differences in heritability

Laramie E. Duncan, +60 more
- 01 Mar 2018 - 
TL;DR: The results demonstrate genetic influences on the development of PTSD, identify shared genetic risk between PTSD and other psychiatric disorders and highlight the importance of multiethnic/racial samples.
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International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci

Caroline M. Nievergelt, +213 more
TL;DR: A GWAS from the Psychiatric Genomics Consortium is reported in which two risk loci in European ancestry and one locus in African ancestry individuals are identified and it is found that PTSD is genetically correlated with several other psychiatric traits.
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A DNA methylation biomarker of alcohol consumption.

Chunyu Liu, +74 more
- 01 Feb 2018 - 
TL;DR: An epigenome-wide association study of methylation of cytosine-phosphate-guanine dinucleotide (CpG) sites in relation to alcohol intake identified a robust alcohol-related DNA methylation signature and shown the potential utility ofDNA methylation as a clinically useful diagnostic test to detect current heavy alcohol consumption.
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Methylation quantitative trait loci (meQTLs) are consistently detected across ancestry, developmental stage, and tissue type

TL;DR: Insight is given into how SNPs impact gene regulation and the notion that peripheral blood may be a reliable correlate of physiological processes in other tissues is supported.
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Accounting for Population Stratification in DNA Methylation Studies

TL;DR: Among the different approaches to computing methylation‐based PCs, it is found that PCs based on CpG sites chosen for their potential to proxy nearby SNPs can provide a powerful and computationally efficient approach to adjust for population stratification in DNA methylation studies when genome‐wide SNP data are unavailable.