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Hettema, J. M.

Publications and source records attributed to Hettema, J. M..

3 recordsLinked to original sources

Gene-drug interactions identify genomic loci that enhance statin effectiveness in lowering LDL cholesterol.

Hyperlipidemia, and high low-density lipoprotein cholesterol (LDL-c) in particular, is a risk factor for cardiovascular disease, including atherosclerosis, myocardial infarction, and stroke. Nearly 200 million people worldwide take HMG-CoA reductase inhibitors, commonly known as statins, to lower their LDL-c. If statins interfere with the genetic pathways that endogenously increase the risk for hyperlipidemia, gene-statin interactions may identify genomic variants, and thereby individuals with those genotypes, that are particularly sensitive to these medications. We performed a series of genome-wide gene-statin interaction analyses in the UK Biobank for LDL-c and two related lipids: high-density lipoprotein cholesterol (HDL-c) and triglycerides (TG). We identified five genome-wide significant gene-statin interactions for LDL-c, two interactions for HDL-c, and four interactions for TG. Importantly, only the SNP-based heritability of LDL-c was reduced by statin use. Using data from All of Us, we replicated all five significant gene-statin interaction loci for LDL-c in the European-like ancestry sample, two loci in the Americas-like ancestry sample, and one locus in the African-like ancestry sample. We also identified fifteen loci that remained associated with LDL-c despite statin treatment, highlighting potential additional genetic targets for drug development, enhancement, and repurposing. These loci include gene-targets for the recently developed hyperlipidemia drug class (PCSK9 inhibitors) validating our approach to finding new treatments. These results are an important step towards personalized medicine for patients with hyperlipidemia. Author SummaryHigh cholesterol raises the risk of heart attacks and strokes and nearly 200 million people worldwide take statins to lower it. While statins work for nearly everyone, they work better for some people than others. We examined how genetic differences enhance the effectiveness of statin medication as a step toward enhancing personalized medicine for those with high cholesterol. By analyzing genetic and health data from about 390,000 people, we found that statins primarily disrupt the link between genes and LDL or "bad" cholesterol levels. Across the genome, statins reduce the impact of genes on LDL-c levels, but not other blood lipids like HDL-c or triglycerides. For LDL-c specifically, we found five regions where genetic differences increase the effectiveness of statins. People with the protective genetic variants are expected to see greater cholesterol reduction with statin use. We confirmed four of the five findings in European-like ancestry samples, with partial replication in Americas-like and African-like ancestry samples (two variants and one variant, respectively). We also found 15 genomic regions where cholesterol stays high despite statin treatment. These genomic regions could be targets for new or enhanced cholesterol medications. In fact, a newer drug class targets one of these regions supporting our approach to finding new treatments.

genetics↗

Twin Study of Early-Onset Major Depression Finds DNA Methylation Enrichment for Neurodevelopmental Genes

Major depression (MD) is a debilitating mental health condition with peak prevalence occurring early in life. Genome-wide examination of DNA methylation (DNAm) offers an attractive comple ment to studies of allelic risk given it can reflect the combined influence of genes and environment. The current study used a co-twin control design to identify differentially and variably methylated regions of the genome that distinguish monozygotic (MZ) twins with and without a lifetime history of early-onset MD. The sample included 150 Caucasian monozygotic twins (73% female; Mage=17.52 SD=1.28) assessed during a developmental stage characterized by relatively dis tinct neurophysiological changes. All twins were generally healthy and currently free of medica tions with psychotropic effects. DNAm was measured in peripheral blood cells using the Infinium Human BeadChip 450K Array. MD associations were detected at 760 differentially and variably methylated probes/regions that mapped to 428 genes. Results indicated an association between early-onset MD and many genes and genomic regions involved in neural circuitry formation, pro jection, functioning, and plasticity. Gene enrichment analyses implicated genes related to neuron structures and neurodevelopmental processes including cell-cell adhesion genes (e.g., CDHs, PCDHAs, PCDHA1C/2C). Genes previously implicated in mood and psychiatric disorders as well as chronic stress (e.g., HDAC4, NRG1) also were identified. DNAm regions associated with MD where found to overlap genetic loci observed in the latest Psychiatric Genomics Consortium meta- analysis of depression. Understanding the time course of epigenetic influences during emerging adulthood may clarify developmental phases where genes modulate individual differences in MD risk.

genetics↗

The Common Genetic Architecture of Anxiety Disorders

Anxiety disorders are common, complex psychiatric disorders with twin heritabilities of 30-60%. We conducted a genome-wide association study of Lifetime Anxiety Disorder (n = 83 565) and an additional Current Anxiety Symptoms (n= 77 125) analysis. The liability scale common variant heritability estimate for Lifetime Anxiety Disorder was 26%, and for Current Anxiety Symptoms was 31%. Five novel genome-wide significant loci were identified including an intergenic region on chromosome 9 that has previously been associated with neuroticism, and a locus overlapping the BDNF receptor gene, NTRK2. Anxiety showed significant genetic correlations with depression and insomnia as well as coronary artery disease, mirroring findings from epidemiological studies. We conclude that common genetic variation accounts for a substantive proportion of the genetic architecture underlying anxiety.

genetics↗