👤 Hugh Stephen Markus

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Also published as: Hugh S Markus, Marcello R P Markus
articles
Matthew Traylor, Elodie Persyn, Liisa Tomppo +43 more · 2021 · The Lancet. Neurology · Elsevier · added 2026-04-24
The genetic basis of lacunar stroke is poorly understood, with a single locus on 16q24 identified to date. We sought to identify novel associations and provide mechanistic insights into the disease. W Show more
The genetic basis of lacunar stroke is poorly understood, with a single locus on 16q24 identified to date. We sought to identify novel associations and provide mechanistic insights into the disease. We did a pooled analysis of data from newly recruited patients with an MRI-confirmed diagnosis of lacunar stroke and existing genome-wide association studies (GWAS). Patients were recruited from hospitals in the UK as part of the UK DNA Lacunar Stroke studies 1 and 2 and from collaborators within the International Stroke Genetics Consortium. Cases and controls were stratified by ancestry and two meta-analyses were done: a European ancestry analysis, and a transethnic analysis that included all ancestry groups. We also did a multi-trait analysis of GWAS, in a joint analysis with a study of cerebral white matter hyperintensities (an aetiologically related radiological trait), to find additional genetic associations. We did a transcriptome-wide association study (TWAS) to detect genes for which expression is associated with lacunar stroke; identified significantly enriched pathways using multi-marker analysis of genomic annotation; and evaluated cardiovascular risk factors causally associated with the disease using mendelian randomisation. Our meta-analysis comprised studies from Europe, the USA, and Australia, including 7338 cases and 254 798 controls, of which 2987 cases (matched with 29 540 controls) were confirmed using MRI. Five loci (ICA1L-WDR12-CARF-NBEAL1, ULK4, SPI1-SLC39A13-PSMC3-RAPSN, ZCCHC14, ZBTB14-EPB41L3) were found to be associated with lacunar stroke in the European or transethnic meta-analyses. A further seven loci (SLC25A44-PMF1-BGLAP, LOX-ZNF474-LOC100505841, FOXF2-FOXQ1, VTA1-GPR126, SH3PXD2A, HTRA1-ARMS2, COL4A2) were found to be associated in the multi-trait analysis with cerebral white matter hyperintensities (n=42 310). Two of the identified loci contain genes (COL4A2 and HTRA1) that are involved in monogenic lacunar stroke. The TWAS identified associations between the expression of six genes (SCL25A44, ULK4, CARF, FAM117B, ICA1L, NBEAL1) and lacunar stroke. Pathway analyses implicated disruption of the extracellular matrix, phosphatidylinositol 5 phosphate binding, and roundabout binding (false discovery rate <0·05). Mendelian randomisation analyses identified positive associations of elevated blood pressure, history of smoking, and type 2 diabetes with lacunar stroke. Lacunar stroke has a substantial heritable component, with 12 loci now identified that could represent future treatment targets. These loci provide insights into lacunar stroke pathogenesis, highlighting disruption of the vascular extracellular matrix (COL4A2, LOX, SH3PXD2A, GPR126, HTRA1), pericyte differentiation (FOXF2, GPR126), TGF-β signalling (HTRA1), and myelination (ULK4, GPR126) in disease risk. British Heart Foundation. Show less
no PDF DOI: 10.1016/S1474-4422(21)00031-4
RAPSN
Julie Hahn, Yi-Ping Fu, Michael R Brown +42 more · 2020 · PloS one · PLOS · added 2026-04-24
Genome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on ca Show more
Genome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To overcome the limited scope that common variants provide, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome. Using samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. For prevalent events, a total of 27,349 participants of European ancestry, including 1831 prevalent MI cases and 2518 prevalent CHD cases were used. For incident cases, a total of 55,736 participants of European ancestry were included (3,031 incident MI cases and 5,425 incident CHD cases). There were 1,860 all-cause deaths among the 3,751 MI and CHD cases from six cohorts that contributed to the analysis of all-cause mortality. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR = 1.80, 95% confidence interval: 1.43, 2.27; P = 7.12 × 10-7). We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) ≥ 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event. This study identified one known locus (ANGPTL4) and four new loci (PLCL1, RC3H2, TMPRSS5, and LDLRAD1) associated with cardiovascular disease risk that warrant further investigation. Show less
📄 PDF DOI: 10.1371/journal.pone.0230035
ANGPTL4
Kolawole Wasiu Wahab, Hemant K Tiwari, Bruce Ovbiagele +6 more · 2019 · Journal of the neurological sciences · Elsevier · added 2026-04-24
Although highly heritable, few genes have been linked to spontaneous intracerebral hemorrhage (SICH), which does not currently have any evidence-based disease-modifying therapy. Individuals of African Show more
Although highly heritable, few genes have been linked to spontaneous intracerebral hemorrhage (SICH), which does not currently have any evidence-based disease-modifying therapy. Individuals of African ancestry are especially susceptible to SICH, even more so for indigenous Africans. We systematically reviewed the genetic variants associated with SICH and examined opportunities for rapidly advancing SICH genomic research for precision medicine. We searched the National Human Genome Research Institute-European Bioinformatics Institute (NHGRI-EBI) Genome Wide Association Study (GWAS) catalog and PubMed for original research articles on genetic variants associated with SICH as of 15 June 2019 using the PRISMA guideline. Eight hundred and sixty-four articles were identified using pre-specified search criteria, of which 64 met the study inclusion criteria. Among eligible articles, only 9 utilized GWAS approach while the rest were candidate gene studies. Thirty-eight genetic loci were found to be variously associated with the risk of SICH, hematoma volume, functional outcome and mortality, out of which 8 were from GWAS including APOE, CR1, KCNK17, 1q22, CETP, STYK1, COL4A2 and 17p12. None of the studies included indigenous Africans. Given this limited information on the genetic contributors to SICH, more genomic studies are needed to provide additional insights into the pathophysiology of SICH, and develop targeted preventive and therapeutic strategies. This call for additional investigation of the pathogenesis of SICH is likely to yield more discoveries in the unexplored indigenous African populations which also have a greater predilection. Show less
📄 PDF DOI: 10.1016/j.jns.2019.116526
CETP
Andrea D Coviello, Robin Haring, Melissa Wellons +96 more · 2012 · PLoS genetics · PLOS · added 2026-04-24
Andrea D Coviello, Robin Haring, Melissa Wellons, Dhananjay Vaidya, Terho Lehtimäki, Sarah Keildson, Kathryn L Lunetta, Chunyan He, Myriam Fornage, Vasiliki Lagou, Massimo Mangino, N Charlotte Onland-Moret, Brian Chen, Joel Eriksson, Melissa Garcia, Yong Mei Liu, Annemarie Koster, Kurt Lohman, Leo-Pekka Lyytikäinen, Ann-Kristin Petersen, Jennifer Prescott, Lisette Stolk, Liesbeth Vandenput, Andrew R Wood, Wei Vivian Zhuang, Aimo Ruokonen, Anna-Liisa Hartikainen, Anneli Pouta, Stefania Bandinelli, Reiner Biffar, Georg Brabant, David G Cox, Yuhui Chen, Steven Cummings, Luigi Ferrucci, Marc J Gunter, Susan E Hankinson, Hannu Martikainen, Albert Hofman, Georg Homuth, Thomas Illig, John-Olov Jansson, Andrew D Johnson, David Karasik, Magnus Karlsson, Johannes Kettunen, Douglas P Kiel, Peter Kraft, Jingmin Liu, Östen Ljunggren, Mattias Lorentzon, Marcello Maggio, Marcello R P Markus, Dan Mellström, Iva Miljkovic, Daniel Mirel, Sarah Nelson, Laure Morin Papunen, Petra H M Peeters, Inga Prokopenko, Leslie Raffel, Martin Reincke, Alex P Reiner, Kathryn Rexrode, Fernando Rivadeneira, Stephen M Schwartz, David Siscovick, Nicole Soranzo, Doris Stöckl, Shelley Tworoger, André G Uitterlinden, Carla H van Gils, Ramachandran S Vasan, H-Erich Wichmann, Guangju Zhai, Shalender Bhasin, Martin Bidlingmaier, Stephen J Chanock, Immaculata De Vivo, Tamara B Harris, David J Hunter, Mika Kähönen, Simin Liu, Pamela Ouyang, Tim D Spector, Yvonne T van der Schouw, Jorma Viikari, Henri Wallaschofski, Mark I McCarthy, Timothy M Frayling, Anna Murray, Steve Franks, Marjo-Riitta Järvelin, Frank H de Jong, Olli Raitakari, Alexander Teumer, Claes Ohlsson, Joanne M Murabito, John R B Perry Show less
Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated wi Show more
Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8 × 10(-106)), PRMT6 (rs17496332, 1p13.3, p = 1.4 × 10(-11)), GCKR (rs780093, 2p23.3, p = 2.2 × 10(-16)), ZBTB10 (rs440837, 8q21.13, p = 3.4 × 10(-09)), JMJD1C (rs7910927, 10q21.3, p = 6.1 × 10(-35)), SLCO1B1 (rs4149056, 12p12.1, p = 1.9 × 10(-08)), NR2F2 (rs8023580, 15q26.2, p = 8.3 × 10(-12)), ZNF652 (rs2411984, 17q21.32, p = 3.5 × 10(-14)), TDGF3 (rs1573036, Xq22.3, p = 4.1 × 10(-14)), LHCGR (rs10454142, 2p16.3, p = 1.3 × 10(-07)), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7 × 10(-08)), and UGT2B15 (rs293428, 4q13.2, p = 5.5 × 10(-06)). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5 × 10(-08), women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ~15.6% and ~8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance. Show less
📄 PDF DOI: 10.1371/journal.pgen.1002805
JMJD1C