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Novel Approach Identifies Two More Genetic Loci for Intracerebral Hemorrhage

Key findings

  • The genetics of intracerebral hemorrhage (ICH) are difficult to study because ICH has a relatively low incidence and high mortality, and disease mechanisms differ for lobar versus non-lobar locations
  • Massachusetts General Hospital researchers devised a novel approach: a genome-wide association study (GWAS) of ICH followed by a combined GWAS of ICH and small vessel ischemic stroke (SVS)
  • The GWAS of ICH confirmed a previously reported genome-wide significant association in the APOE region for lobar ICH
  • Through a meta-analysis of the ICH results with the results of a previously published GWAS of SVS, the researchers found genome-wide significant associations for non-lobar ICH at three loci, including two novel loci
  • This novel genome-wide approach might improve understanding of the mechanisms of cerebral small vessel disease and lead to new strategies for prevention and treatment

Cerebral small vessel disease (CSVD) is a major contributor to vascular cognitive impairment, late-life gait disorders and depression. There are no preventive strategies besides managing hypertension, and no effective treatments are known. In order to develop an effective therapy, it's vital to uncover the mechanisms of the disease.

The most acute manifestations of CSVD are small-vessel ischemic stroke (SVS) and intracerebral hemorrhage (ICH). The heritability of these correlated diseases is substantial—at least 29% for ICH and 16% for SVS—but relatively few genetic variants have been identified for either of them. ICH is particularly difficult to study because it has a relatively low incidence and high mortality, and disease mechanisms differ for lobar versus non-lobar ICH.

Christopher D. Anderson, MD, director of Acute Stroke Services and researcher at the Center for Genomic MedicineJonathan Rosand, MD, co-director of Mass General Neuroscience and the Henry and Allison McCance Center for Brain Health at Massachusetts General Hospital, and Jaeyoon Chung, PhD, of Boston University, and colleagues devised a novel approach to studying the genetics of ICH: a combined genome-wide association study (GWAS) of SVS and ICH. In Brain, they describe their methodology and report two novel loci for ICH.

Study Details

To improve their ability to study ICH, the research team created a larger sample size through cross-phenotype analysis. They estimated the polygenic structure shared by ICH and SVS, then combined and weighted the genetic associations of the variants from the two diseases according to the degree of genetic overlap.


The researchers first performed a GWAS in 1,813 subjects with ICH (755 lobar, 1,005 non-lobar) and 1,711 stroke-free control subjects. For lobar ICH, they observed genome-wide significant associations in the APOE region, which was reported as being associated with ICH.

No genome-wide significant associations were found for non-lobar ICH or all ICH.

Multi-Trait Analysis

Through a novel meta-analysis approach, the team analyzed the ICH results by location with the results of a previously published GWAS of 237,511 individuals with SVS that Dr. Anderson and Dr. Rosand previously co-authored. That led to a sample size of 241,024 individuals: 6,255 with ICH or SVS and 233,058 control subjects.

No genome-wide significant associations were found for lobar ICH or for all ICH cases in this meta-analysis. However, for non-lobar ICH, the analysis revealed genome-wide significant associations with single nucleotide polymorphisms (SNPs) at three loci, including two novel loci:

  • 2q33—associated with 10 SNPs within ICA1L (best-associated SNP: rs72932727)
  • 13q34—nine SNPs within COL4A2 (best SNP: rs9515201)
  • 1q22 (previously reported to be associated with ICH)—five SNPs between SLC25A44 and PMF1 (best SNP: rs2758605)

A Useful Solution

The discovery of two novel loci, plus confirmation of two previously reported loci, speaks to the credibility of combined GWASs of ICH and SVS. This approach may improve the statistical power to detect additional genetic factors in CSVD and other prevalent diseases of aging that share genetic liability across traits.

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