Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jul 27;12(1):4571.
doi: 10.1038/s41467-021-24563-1.

GWAS of serum ALT and AST reveals an association of SLC30A10 Thr95Ile with hypermanganesemia symptoms

Collaborators, Affiliations

GWAS of serum ALT and AST reveals an association of SLC30A10 Thr95Ile with hypermanganesemia symptoms

Lucas D Ward et al. Nat Commun. .

Abstract

Understanding mechanisms of hepatocellular damage may lead to new treatments for liver disease, and genome-wide association studies (GWAS) of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) serum activities have proven useful for investigating liver biology. Here we report 100 loci associating with both enzymes, using GWAS across 411,048 subjects in the UK Biobank. The rare missense variant SLC30A10 Thr95Ile (rs188273166) associates with the largest elevation of both enzymes, and this association replicates in the DiscovEHR study. SLC30A10 excretes manganese from the liver to the bile duct, and rare homozygous loss of function causes the syndrome hypermanganesemia with dystonia-1 (HMNDYT1) which involves cirrhosis. Consistent with hematological symptoms of hypermanganesemia, SLC30A10 Thr95Ile carriers have increased hematocrit and risk of iron deficiency anemia. Carriers also have increased risk of extrahepatic bile duct cancer. These results suggest that genetic variation in SLC30A10 adversely affects more individuals than patients with diagnosed HMNDYT1.

PubMed Disclaimer

Conflict of interest statement

A.D., A.F.C., S.T., L.W., M.P., P.N., C.Q., H.C.T., G.H., and P.H. are employees of Alnylam Pharmaceuticals, Inc. L.L., N.V., M.F., and A.B. are employees of Regeneron Pharmaceuticals, Inc.

Figures

Fig. 1
Fig. 1. Manhattan plots showing trans-ancestry GWAS results for ALT and AST.
Red dots indicate lead variants for shared signals between the two GWAS; for clarity, the shared signals are marked only once, on the plot for the GWAS in which the more significant association is detected. Cis-pQTLs (at GPT and GOT2) are labeled in blue. Loci with shared signals are labeled (for clarity, only when p < 10−25 and only on the GWAS for which the association is most significant). Loci previously reported to associate with both ALT and AST are named in bold. SLC30A10, the main topic of this report, is labeled in red on both plots. Source data for this figure are available from NHGRI-EBI GWAS catalog accession GCST90013663 and GCST90013664.
Fig. 2
Fig. 2. Classification of the top ALT- and AST- associated loci based on annotations.
Unless otherwise noted with an asterisk, loci are named by the closest protein-coding gene. “Coding” indicates that one of the variants linked to the lead variant is predicted to have a moderate or high impact on a protein-coding gene. “Liver eQTL” and “Muscle or kidney eQTL” indicate that one of the variants linked to the lead variant is the strongest eQTL for a gene in those tissues by GTEx. Loci are further categorized as followed: asterisk, indicating the locus is named for a gene other than the closest to the lead variant, due to coding or eQTL annotation; gray, indicating the lead variant is over 100 kilobases from a protein-coding gene; bold, indicating a known GWAS catalog ALT or AST locus; bold and underlined, indicating a known GWAS catalog ALT and AST locus. Source data for this figure are in Supplementary Data 2.
Fig. 3
Fig. 3. Comparison of effect of lead variants on ALT and AST with effect on liver disease.
Effect sizes (beta from the regression of units of log10 ALT and AST, equivalent to percent change; and beta from the liver disease regression, equivalent to natural log of the odds ratio) are from PLINK analysis; error bars are 95% confidence intervals on these effect sizes from PLINK. Source data for this figure are in Supplementary Data 2.
Fig. 4
Fig. 4. Miami plot of trans-ancestry SAIGE GWAS results within 1 Mb of the gene body of SLC30A10.
ALT associations are shown in the positive direction and AST associations in the negative direction. Variant associations reaching genome-wide significance for one enzyme are colored black; for both enzymes, colored red; directly-genotyped variants significant for both enzymes, red diamonds. Source data for this figure are available from NHGRI-EBI GWAS catalog accession GCST90013663 and GCST90013664.
Fig. 5
Fig. 5. GWAS of extrahepatic bile duct cancer.
P values are from SAIGE in White British. Dashed line is genome-wide significance level of p = 5 × 10−8. Source data for this figure are available from NHGRI-EBI GWAS catalog accession GCST90013662.
Fig. 6
Fig. 6. Immunofluorescence imaging of SLC30A10 protein constructs expressed in cultured HeLa cells.
WT = wild type (ad); T95I = Thr95Ile (eh); Δ105–107 (il) and L89P (mp), HMNDYT1-causing variants reported previously; empty = transfected with empty vector (qt); NTC = non transfected control (ux). Calnexin staining (in red) indicates the endoplasmic reticulum (ER). Color balance has been adjusted globally to improve the contrast between channels in overlay images; original unadjusted micrographs are provided as a Source data file.
Fig. 7
Fig. 7. Relationship of Mendelian and common-variant GWAS phenotypes at the SLC30A10 locus.
Phenotypes are summarized for HMNDYT1-causing variants, SLC30A10 Thr95Ile, and GWAS variants.

References

    1. Asrani SK, Devarbhavi H, Eaton J, Kamath PS. Burden of liver diseases in the world. J. Hepatol. 2019;70:151–171. doi: 10.1016/j.jhep.2018.09.014. - DOI - PubMed
    1. Younossi ZM, et al. Changes in the prevalence of the most common causes of chronic liver diseases in the United States from 1988 to 2008. Clin. Gastroenterol. Hepatol. 2011;9:524–530.e1; quiz e60. doi: 10.1016/j.cgh.2011.03.020. - DOI - PubMed
    1. Plenge RM, Scolnick EM, Altshuler D. Validating therapeutic targets through human genetics. Nat. Rev. Drug Disco. 2013;12:581–594. doi: 10.1038/nrd4051. - DOI - PubMed
    1. Stevens JL, Baker TK. The future of drug safety testing: expanding the view and narrowing the focus. Drug Disco. Today. 2009;14:162–167. doi: 10.1016/j.drudis.2008.11.009. - DOI - PubMed
    1. Deaton AM, et al. Rationalizing secondary pharmacology screening using human genetic and pharmacological evidence. Toxicol. Sci. 2019;167:593–603. doi: 10.1093/toxsci/kfy265. - DOI - PMC - PubMed

MeSH terms