Essential fatty acid metabolism in myeloid cells plays a critical but underexplored role in immune function. Here, we demonstrate that simultaneous inactivation of two key enzymes involved in macrophage polyunsaturated fatty acid (PUFA) metabolism-ELOVL5, which elongates long-chain PUFAs, and LPCAT3, which incorporates them into phospholipids-disrupts membrane organization by promoting the formation of cholesterol-enriched domains. This increases macrophage sensitivity to cytotoxic oxysterols and leads to more vulnerable atherosclerotic plaques with enlarged necrotic cores in a mouse model of atherosclerosis. In humans, analysis of 187 carotid plaques reveals a positive correlation between LPCAT3/ELOVL5-generated phospholipids-including arachidonate (C20:4 n-6)-containing ether lipids-and more stable plaque profiles. Additionally, Mendelian randomization analysis supports a causal relationship between LPCAT3 expression and reduced risk of ischemic stroke. Our findings uncover a regulatory circuit essential for PUFA-containing phospholipid generation in macrophages, positioning PUFA-containing ether lipids as promising biomarkers and therapeutic targets.

Substance use has been associated with differences in adult brain morphology; however, it is unclear whether these differences precede or are a result of substance use substance use. We investigated the impact of polygenic risk scores (PRSs) for cannabis use disorder (CUD) and general substance use and substance use disorder liability (SU/SUD) on brain morphology in drug-naïve adolescents. Baseline data were used from 1,874 European-descent participants (ages 9-11) comprising 222, 328 and 387 pairs of MZ twins, DZ twins, and Non-Twin Siblings, respectively, in the Adolescent Brain Cognitive Development Study. We fitted multivariate twin models to estimate the putative effects of CUD, SU/SUD, and brain region-specific PRSs. These models assessed their influence on six subcortical and two cortical phenotypes. PRS for CUD and SU/SUD were created based on GWAS conducted by Johnson et al. (2020) and Hatoum et al. (2023), respectively. When decomposing variance in each brain region of interest (ROI), we used the corresponding ROI-specific PRS. Brain morphometry in drug-naive subjects was unrelated to CUD PRS. The variance explained in each ROI by its corresponding PRS ranged from 0.8-4.4%. The SU/SUD PRS showed marginally significant effects (0.2-0.4%) on cortical surface area and nucleus accumbens volume, but overall effect sizes were small. Our findings indicate that differences in brain morphometry among baseline drug-naive individuals are not associated with the genetic risk for CUD but show a weak association with general addiction and substance use risk (SU/SUD), particularly in nucleus accumbens volume and total cortical surface area.

This review highlights contributions of the Global Lipids Genetics Consortium (GLGC) in advancing the understanding of the genetic etiology of blood lipid traits, including total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, and non-HDL cholesterol. We emphasize the consortium's collaborative efforts, discoveries related to lipid and lipoprotein biology, methodological advancements, and utilization in areas extending beyond lipid research.

The GLGC has identified over 923 genomic loci associated with lipid traits through genome-wide association studies (GWASs), involving more than 1.65 million individuals from globally diverse populations. Many loci have been functionally validated by individuals inside and outside the GLGC community. Recent GLGC studies show increased population diversity enhances variant discovery, fine-mapping of causal loci, and polygenic score prediction for blood lipid levels. Moreover, publicly available GWAS summary statistics have facilitated the exploration of lipid-related genetic influences on cardiovascular and noncardiovascular diseases, with implications for therapeutic development and drug repurposing.

The GLGC has significantly advanced the understanding of the genetic basis of lipid levels and serves as the leading resource of GWAS summary statistics for these traits. Continued collaboration will be critical to further understand lipid and lipoprotein biology through large-scale genetic assessments in diverse populations.

Obesity is associated with adverse effects on health and quality of life. Improved understanding of its underlying pathophysiology is essential for developing counteractive measures. To search for sequence variants with large effects on BMI, we perform a multi-ancestry meta-analysis of 13 genome-wide association studies on BMI, including data derived from 1,534,555 individuals of European ancestry, 339,657 of Asian ancestry, and 130,968 of African ancestry. We identify an intergenic 262,760 base pair deletion at the MC4R locus that associates with 4.11 kg/m2 higher BMI per allele, likely through downregulation of MC4R. Moreover, a rare FRS3 missense variant, p.Glu115Lys, only found in individuals from Finland, associates with 1.09 kg/m2 lower BMI per allele. We also detect three other low-frequency FRS3 missense variants that associate with BMI with smaller effects and are enriched in different ancestries. We characterize FRS3 as a BMI-associated gene, encoding an adaptor protein known to act downstream of BDNF and TrkB, which regulate appetite, food intake, and energy expenditure through unknown signaling pathways. The work presented here contributes to the biological foundation of obesity by providing a convincing downstream component of the BDNF-TrkB pathway, which could potentially be targeted for obesity treatment.

Calcific aortic valve disease (CAVD), and ensuing severe aortic stenosis (AS), is the foremost valvular disorder of aging, yet preventive therapies are lacking. A better understanding of the molecular underpinnings of aortic valve calcification (AVC) is necessary to develop pharmacologic interventions.

We undertook large-scale plasma proteomics in a cohort study of adults ≥65 years old, the CHS (Cardiovascular Health Study), to identify individual proteins associated with echocardiographic AVC and incident moderate/severe AS. Proteomics measurements were performed with the aptamer-based SomaLogic platform of ~5000 proteins. Significant proteins were validated in a second cohort, the AGES-RS (Age, Gene/Environment Susceptibility-Reykjavik Study), which assessed AVC and AS by computed tomography. The potential causal associations of replicated proteins were tested in 2-sample Mendelian randomization using identified cis protein quantitative trait loci in consortia having computed tomography-quantified AVC or AS as outcomes. Six proteins showed Bonferroni-corrected significant relationships with AVC in CHS. Three of these, CXCL-12 (C-X-C chemokine ligand 12), KLKB1 (kallikrein), and leptin, replicated in AGES-RS, of which the former 2 are novel. Only 1 protein, CXCL6, which showed a near-significant association with AS in the replication cohort, was significantly (positively) associated with incident AS. Mendelian randomization analysis was conducted for KLKB1, CXCL12, and CXCL6, which supported a causal relationship for higher KLKB1 with lower AVC (beta=-0.25, P=0.009).

This study of older adults newly identified and largely replicated associations of 3 circulating proteins with calcific aortic valve disease, of which the relationship of plasma KLKB1 may have a causal basis. Additional investigation is necessary to determine if KLKB1 could be harnessed for calcific aortic valve disease therapeutics.

Precision medicine provides patients with access to personally tailored treatments based on individual-level data. However, developing personalized therapies requires analyses with substantial statistical power to map genetic and epidemiologic associations that ultimately create models informing clinical decisions. As one solution, biobanks have emerged as large-scale, longitudinal cohort studies with long-term storage of biological specimens and health information, including electronic health records and participant survey responses. By providing access to individual-level data for genotype-phenotype mapping efforts, pharmacogenomic studies, polygenic risk score assessments and rare variant analyses, biobanks support ongoing and future precision medicine research. Notably, due in part to the geographical enrichment of biobanks in Western Europe and North America, European ancestries have become disproportionately over-represented in precision medicine research. Herein, we provide a genetics-focused review of biobanks from around the world that are in pursuit of supporting precision medicine. We discuss the limitations of their designs, ongoing efforts to diversify genomics research and strategies to maximize the benefits of research leveraging biobanks for all.

As awareness of dementia increases, more individuals with minor cognitive complaints are requesting clinical assessment. Neuroimaging studies frequently identify incidental white matter hyperintensities, raising patient concerns about their brain health and future risk for dementia. Moreover, current US demographics indicate that ≈50% of these individuals will be from diverse backgrounds by 2060. Racial and ethnic minority populations bear a disproportionate burden of vascular risk factors magnifying dementia risk. Despite established associations between white matter hyperintensities and cognitive impairment, including dementia, no study has comprehensively and prospectively examined the impact of individual and combined magnetic resonance imaging measures of white matter injury, their risk factors, and comorbidities on cognitive performance among a diverse, nondemented, stroke-free population with cognitive complaints over an extended period of observation. The Diverse VCID (Diverse Vascular Cognitive Impairment and Dementia) study is designed to fill this knowledge gap through 3 assessments of clinical, behavioral, and risk factors; neurocognitive and magnetic resonance imaging measures; fluid biomarkers of Alzheimer disease, vascular inflammation, angiogenesis, and endothelial dysfunction; and measures of genetic risk collected prospectively over a minimum of 3 years in a cohort of 2250 individuals evenly distributed among Americans of Black/African, Latino/Hispanic, and non-Hispanic White backgrounds. The goal of this study is to investigate the basic mechanisms of small vessel cerebrovascular injury, emphasizing clinically relevant assessment tools and developing a risk score that will accurately identify at-risk individuals for possible treatment or clinical therapeutic trials, particularly individuals of diverse backgrounds where vascular risk factors and disease are more prevalent.

Despite the blaze of advancing knowledge on its complex genetic architecture, hypertension remains an elusive condition. Genetic studies of blood pressure have yielded bitter-sweet results thus far with the identification of more than 2,000 genetic loci, though the candidate causal genes and biological pathways remain largely unknown. The era of big data and sophisticated statistical tools has propelled insights into pathophysiology and causal inferences. However, new genetic risk tools for hypertension are the tip of the iceberg, and applications of genomic technology are likely to proliferate. We review the genomics of hypertension, exploring the significant milestones in our current understanding of this condition and the progress towards personalised treatment and management for hypertension.

Cerebral small vessel disease (cSVD) causes lacunar stroke (LS), intracerebral haemorrhage, and is the most common pathology underlying vascular dementia. However, there are few trials examining whether treating conventional cardiovascular risk factors reduce stroke risk in cSVD, as opposed to stroke as a whole. We used Mendelian randomization techniques to investigate which risk factors are causally related to cSVD and to evaluate whether specific drugs may be beneficial in cSVD prevention. We identified genetic proxies for blood pressure traits, lipids, glycaemic markers, anthropometry measures, smoking, alcohol consumption, and physical activity from large-scale genome-wide association studies of European ancestry. We also selected genetic variants as proxies for drug target perturbation in hypertension, dyslipidaemia, hyperglycaemia, and obesity. Mendelian randomization was performed to assess their associations with LS from the GIGASTROKE Consortium (n = 6811) and in a sensitivity analysis in a cohort of patients with MRI-confirmed LS (n = 3306). We also investigated associations with three neuroimaging features of cSVD, namely, white matter hyperintensities (n = 55 291), fractional anisotropy (n = 36 460), and mean diffusivity (n = 36 012). Genetic predisposition to higher systolic and diastolic blood pressure was associated with LS and cSVD imaging markers. Genetically predicted liability to diabetes, obesity, smoking, higher triglyceride levels, and the ratio of triglycerides to high density lipoprotein (HDL) also showed detrimental associations with LS risk, while genetic predisposition to higher HDL concentrations and moderate-to-vigorous physical activity showed protective associations. Genetically proxied blood pressure-lowering through calcium channel blockers (CCBs) was associated with cSVD imaging markers, while genetically proxied HDL-raising through Cholesteryl Ester Transfer Protein (CETP) inhibitors, triglyceride-lowering through lipoprotein lipase (LPL), and weight-lowering through gastric inhibitory polypeptide receptor (GIPR) were associated with lower risk of LS. Our findings highlight the importance of some conventional cardiovascular risk factors, including blood pressure and BMI, in cSVD, but not other e.g. LDL. The findings further demonstrate the potential beneficial effects of CCBs on cSVD imaging markers and CETP inhibitors, LPL enhancement, and GIPR obesity-targeted drugs on LS. They provide useful information for initiating future clinical trials examining secondary prevention strategies in cSVD.

Genetic studies have identified numerous regions associated with plasma fibrinogen levels in Europeans, yet missing heritability and limited inclusion of non-Europeans necessitates further studies with improved power and sensitivity. Compared with array-based genotyping, whole-genome sequencing (WGS) data provide better coverage of the genome and better representation of non-European variants. To better understand the genetic landscape regulating plasma fibrinogen levels, we meta-analyzed WGS data from the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program (n = 32 572), with array-based genotype data from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (n = 131 340) imputed to the TOPMed or Haplotype Reference Consortium panel. We identified 18 loci that have not been identified in prior genetic studies of fibrinogen. Of these, 4 are driven by common variants of small effect with reported minor allele frequency (MAF) at least 10 percentage points higher in African populations. Three signals (SERPINA1, ZFP36L2, and TLR10) contain predicted deleterious missense variants. Two loci, SOCS3 and HPN, each harbor 2 conditionally distinct, noncoding variants. The gene region encoding the fibrinogen protein chain subunits (FGG;FGB;FGA) contains 7 distinct signals, including 1 novel signal driven by rs28577061, a variant common in African ancestry populations but extremely rare in Europeans (MAFAFR = 0.180; MAFEUR = 0.008). Through phenome-wide association studies in the VA Million Veteran Program, we found associations between fibrinogen polygenic risk scores and thrombotic and inflammatory disease phenotypes, including an association with gout. Our findings demonstrate the utility of WGS to augment genetic discovery in diverse populations and offer new insights for putative mechanisms of fibrinogen regulation.

Factor V (FV) is a key molecular player in the coagulation cascade. FV plasma levels have been associated with several human diseases, including thrombosis, bleeding, and diabetic complications. So far, 2 genes have been robustly found through genome-wide association analyses to contribute to the inter-individual variability of plasma FV levels: structural F5 gene and PLXDC2.

The authors used the underestimated Brown-Forsythe methodology implemented in the QuickTest software to search for non-additive genetic effects that could contribute to the inter-individual variability of FV plasma activity. QUICKTEST was applied to 4 independent genome-wide association studies studies (LURIC [Ludwigshafen RIsk and Cardiovascular Health Study], MARTHA [Marseille Thrombosis Association], MEGA [Multiple Environmental and Genetic Assessment], and RETROVE [Riesgo de Enfermedad Tromboembolica Venosa]) totaling 4505 participants of European ancestry with measured FV plasma levels. Results obtained in the 4 cohorts were meta-analyzed using a fixed-effect model. Additional analyses involved exploring haplotype and gene×gene interactions in downstream investigations. A genome-wide significant signal at the PSKH2 locus on chr8q21.3 with lead variant rs75463553 with no evidence for heterogeneity across cohorts was observed (P=0.518). Although rs75463553 did not show an association with mean FV levels (P=0.49), it demonstrated a robust significant (P=3.38x10-9) association with the variance of FV plasma levels. Further analyses confirmed the reported association of PSKH2 with neutrophil biology and revealed that rs75463553 likely interacts with two loci, GRIN2A and POM121L12, known for their involvement in smoking biology.

This comprehensive approach identifies the role of PSKH2 as a novel molecular player in the genetic regulation of FV, shedding light on the contribution of neutrophils to FV biology.

White matter hyperintensities index structural abnormalities in the cerebral white matter, including axonal damage. The latter may promote atrophy of the cerebral cortex, a key feature of dementia. Here, we report a study of 51,065 individuals from 10 cohorts demonstrating that higher white matter hyperintensity volume associates with lower cortical thickness. The meta-GWAS of white matter hyperintensities-associated cortical 'atrophy' identifies 20 genome-wide significant loci, and enrichment in genes specific to vascular cell types, astrocytes, and oligodendrocytes. White matter hyperintensities-associated cortical 'atrophy' showed positive genetic correlations with vascular-risk traits and plasma biomarkers of neurodegeneration, and negative genetic correlations with cognitive functioning. 15 of the 20 loci regulated the expression of 54 genes in the cerebral cortex that, together with their co-expressed genes, were enriched in biological processes of axonal cytoskeleton and intracellular transport. The white matter hyperintensities-cortical thickness associations were most pronounced in cortical regions with higher expression of genes specific to excitatory neurons with long-range axons traversing through the white matter. The meta-GWAS-based polygenic risk score predicts vascular and all-cause dementia in an independent sample of 500,348 individuals. Thus, the genetics of white matter hyperintensities-related cortical atrophy involves vascular and neuronal processes and increases dementia risk.

Subcortical brain structures are involved in developmental, psychiatric and neurological disorders. Here we performed genome-wide association studies meta-analyses of intracranial and nine subcortical brain volumes (brainstem, caudate nucleus, putamen, hippocampus, globus pallidus, thalamus, nucleus accumbens, amygdala and the ventral diencephalon) in 74,898 participants of European ancestry. We identified 254 independent loci associated with these brain volumes, explaining up to 35% of phenotypic variance. We observed gene expression in specific neural cell types across differentiation time points, including genes involved in intracellular signaling and brain aging-related processes. Polygenic scores for brain volumes showed predictive ability when applied to individuals of diverse ancestries. We observed causal genetic effects of brain volumes with Parkinson's disease and attention-deficit/hyperactivity disorder. Findings implicate specific gene expression patterns in brain development and genetic variants in comorbid neuropsychiatric disorders, which could point to a brain substrate and region of action for risk genes implicated in brain diseases.

Clonal hematopoiesis of indeterminate potential (CHIP) is linked to diverse aging-related diseases, including hematologic malignancy and atherosclerotic cardiovascular disease (ASCVD). While CHIP is common among older adults, the underlying factors driving its development are largely unknown. To address this, we performed whole-exome sequencing on 8,374 blood DNA samples collected from 4,187 Atherosclerosis Risk in Communities Study (ARIC) participants over a median follow-up of 21 years. During this period, 735 participants developed incident CHIP. Splicing factor genes (SF3B1, SRSF2, U2AF1, and ZRSR2) and TET2 CHIP grow significantly faster than DNMT3A non-R882 clones. We find that age at baseline and sex significantly influence the incidence of CHIP, while ASCVD and other traditional ASCVD risk factors do not exhibit such associations. Additionally, baseline synonymous passenger mutations are strongly associated with CHIP status and are predictive of new CHIP clone acquisition and clonal growth over extended follow-up, providing valuable insights into clonal dynamics of aging hematopoietic stem and progenitor cells. This study also reveals associations between germline genetic variants and incident CHIP. Our comprehensive longitudinal assessment yields insights into cell-intrinsic and -extrinsic factors contributing to the development and progression of CHIP clones in older adults.