Expressive

rs117015177 - PKNOX2

Magnitude 2.0 · 2 studies on file

Reported associations

  • Key genetic variants associated with variation of milk oligosaccharides from diverse human populations. - Genomics (2022) · Williams JE, McGuire MK, Meehan CL, McGuire MA, Brooker SL, Kamau-Mbuthia EW, Kamundia EW, Mbugua S, Moore SE, Prentice AM, Otoo GE, Rodríguez JM, Pareja RG, Foster JA, Sellen DW, Kita DG, Neibergs HL, Murdoch BM · PubMed 33831438

    Human milk oligosaccharides (HMO), the third most abundant component of human milk, are thought to be important contributors to infant health. Studies have provided evidence that geography, stage of lactation, and Lewis and secretor blood groups are associated with HMO profile. However, little is known about how variation across the genome may influence HMO composition among women in various populations. In this study, we performed genome-wide association analyses of 395 women from 8 countries to identify genetic regions associated with 19 different HMO. Our data support FUT2 as the most significantly associated (P < 4.23 to P < 4.5 ) gene with seven HMO and provide evidence of balancing selection for FUT2. Although polymorphisms in FUT3 were also associated with variation in lacto-N-f

  • Pan-cancer and cross-population genome-wide association studies dissect shared genetic backgrounds underlying carcinogenesis - Unknown journal (n.d.) · Unknown authors · PubMed 37340002

    ABSTRACT: Integrating genomic data of multiple cancers allows de novo cancer grouping and elucidating the shared genetic basis across cancers. Here, we conduct the pan-cancer and cross-population genome-wide association study (GWAS) meta-analysis and replication studies on 13 cancers including 250,015 East Asians (Biobank Japan) and 377,441 Europeans (UK Biobank). We identify ten cancer risk variants including five pleiotropic associations (e.g., rs2076295 at DSP on 6p24 associated with lung cancer and rs2525548 at TRIM4 on 7q22 nominally associated with six cancers). Quantifying shared heritability among the cancers detects positive genetic correlations between breast and prostate cancer across populations. Common genetic components increase the statistical power, and the large-scale meta

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