Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores.

We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model's performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1 to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8 to 5.1% (SBP) and 4.7 to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs. In summary, non-linear ML models improves BP prediction in models incorporating diverse populations.

Whole genome sequencing based analysis of inflammation biomarkers in the Trans-Omics for Precision Medicine (TOPMed) consortium.

Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38 465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program (with varying sample size by trait, where the minimum sample size was n = 737 for MMP-1). We identified 22 distinct single-variant associations across 6 traits-E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin-that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.

Determinants of mosaic chromosomal alteration fitness.

Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate as PACER scores for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our mCA fitness estimates, derived by aggregating per-individual PACER scores, were correlated (R2 = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using population-level distributions of clonal fraction. Among individuals with JAK2 V617F clonal hematopoiesis of indeterminate potential or mCAs affecting the JAK2 gene on chromosome 9, PACER score was strongly correlated with erythrocyte count. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified a TCL1A locus variant associated with mCA clonal expansion rate, with suggestive variants in NRIP1 and TERT.

Genomic and phenotypic correlates of mosaic loss of chromosome Y in blood.

Mosaic loss of Y (mLOY) is the most common somatic chromosomal alteration detected in human blood. The presence of mLOY is associated with altered blood cell counts and increased risk of Alzheimer's disease, solid tumors, and other age-related diseases. We sought to gain a better understanding of genetic drivers and associated phenotypes of mLOY through analyses of whole genome sequencing of a large set of genetically diverse males from the Trans-Omics for Precision Medicine (TOPMed) program. This approach enabled us to identify differences in mLOY frequencies across populations defined by genetic similarity, revealing a higher frequency of mLOY in the European American (EA) ancestry group compared to those of Hispanic American (HA), African American (AA), and East Asian (EAS) ancestry. Further, we identified two genes ( CFHR1 and LRP6 ) that harbor multiple rare, putatively deleterious variants associated with mLOY susceptibility, show that subsets of human hematopoietic stem cells are enriched for activity of mLOY susceptibility variants, and that certain alleles on chromosome Y are more likely to be lost than others.

Acute pharmacodynamic responses to sitagliptin: Drug-induced increase in early insulin secretion in oral glucose tolerance test.

DPP4 inhibitors are widely prescribed as treatments for type 2 diabetes. Because drug responses vary among individuals, we initiated investigations to identify genetic variants associated with the magnitude of drug responses. Sitagliptin (100 mg) was administered to 47 healthy volunteers. Several endpoints were measured to assess clinically relevant responses - including the effect of sitagliptin on glucose and insulin levels during an oral glucose tolerance test (OGTT). This pilot study confirmed that sitagliptin (100 mg) decreased the area under the curve for glucose during an OGTT (p = 0.0003). Furthermore, sitagliptin promoted insulin secretion during the early portion of the OGTT as reflected by an increase in the ratio of plasma insulin at 30 min divided by plasma insulin at 60 min (T30:T60) from mean ± SEM 0.87 ± 0.05 to 1.62 ± 0.36 mU/L (p = 0.04). The magnitude of sitagliptin's effect on insulin secretion (as judged by the increase in the T30:T60 ratio for insulin) was correlated with the magnitude of sitagliptin-induced increase in the area under the curve for intact plasma GLP1 levels during the first hour of the OGTT. This study confirmed previously reported sex differences in glucose and insulin levels during an OGTT. Specifically, females exhibited higher levels of glucose and insulin at the 90-180 min time points. However, we did not detect significant sex-associated differences in the magnitude of sitagliptin-induced changes in T30:T60 ratios for either glucose or insulin. In conclusion, T30:T60 ratios for insulin and glucose during an OGTT provide useful indices to assess pharmacodynamic responses to DPP4 inhibitors.

Causal Factors for Osteoarthritis: A Scoping Review of Mendelian Randomization Studies.

OBJECTIVE: Mendelian randomization (MR) has increasingly been utilized as a tool for establishing causal relations between modifiable exposures and osteoarthritis (OA). The goal of this review was to summarize available MR studies of OA that evaluate the causal role of modifiable risk factors on OA. METHODS: This review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Extension for Scoping Reviews model. We performed a literature search for relevant studies published before December 2021 across multiple databases using the search terms "osteoarthritis" and ("Mendelian randomization" or "polygenic risk score"). We reported the MR estimates of causal associations between exposures and OA and then assessed methodologic quality of abstracted studies according to their efforts to validate the three key MR assumptions. RESULTS: Our search identified 45 studies reporting on 141 exposure-association analyses. All studies performed a formal instrumental variable analysis to estimate the causal effect of exposure on OA. Causal associations (P < 0.05) were reported in 60 of these analyses representing 36 unique publications, and MR-Egger sensitivity analyses were performed in 45 of these analyses. MR studies provided support for causal associations of OA with increased levels of adiposity, coffee consumption, bone mineral density, and sleep disturbance, and decreased levels of serum calcium and low-density lipoprotein cholesterol. CONCLUSION: These results highlight the potential benefits of weight reduction and improvement of sleep quality to reduce the risk of OA and call for a better understanding of the relations of coffee consumption and serum calcium to OA risk.

Polygenic Risk Score Associates With Atherosclerotic Plaque Characteristics at Autopsy.

BACKGROUND: Polygenic risk scores (PRSs) for coronary artery disease (CAD) potentially improve cardiovascular risk prediction. However, their relationship with histopathologic features of CAD has never been examined systematically. METHODS: From 4327 subjects referred to CVPath by the State of Maryland Office Chief Medical Examiner for sudden death between 1994 and 2015, 2455 cases were randomly selected for genotyping. We generated PRS from 291 known CAD risk loci. Detailed histopathologic examination of the coronary arteries was performed in all subjects. The primary study outcome measurements were histopathologic plaque features determining severity of atherosclerosis, including %stenosis, calcification, thin-cap fibroatheromas, and thrombotic CAD. RESULTS: After exclusion of cases with insufficient DNA sample quality or with missing data, 954 cases (mean age, 48.8±14.7 years; 75.7% men) remained in the final study cohort. Subjects in the highest PRS quintile exhibited more severe atherosclerosis compared with subjects in the lowest quintile, with greater %stenosis (80.3%±27.0% versus 50.4%±38.7%; adjusted P<0.001) and a higher frequency of calcification (69.6% versus 35.8%; adjusted P=0.004) and thin-cap fibroatheroma (26.7% versus 9.5%; adjusted P=0.007). Even after adjustment for traditional CAD risk factors, subjects within the highest PRS quintile had higher odds of severe atherosclerosis (ie, ≥75% stenosis; adjusted odds ratio, 3.77 [95% CI, 2.10-6.78]; P<0.001) and plaque rupture (adjusted odds ratio, 4.05 [95% CI, 2.26-7.24]; P<0.001). Moreover, subjects within the highest quintile had higher odds of CAD-associated cause of death, especially among those aged ≤50 years (adjusted odds ratio, 4.08 [95% CI, 2.01-8.30]; P<0.001). No statistically significant associations were observed with plaque erosion after adjusting for covariates. CONCLUSIONS: This is the first autopsy study investigating associations between PRS and atherosclerosis severity at the histopathologic level in subjects with sudden death. Our pathological analysis suggests PRS correlates with plaque burden and features of advanced atherosclerosis and may be useful as a method for CAD risk stratification, especially in younger subjects.

Evidence of survival bias in the association between APOE-ϵ4 and age of ischemic stroke onset.

Large genome-wide association studies (GWAS) employing case-control study designs have now identified tens of loci associated with ischemic stroke (IS). As a complement to these studies, we performed GWAS in a case-only design to identify loci influencing age at onset (AAO) of ischemic stroke. Analyses were conducted in a Discovery cohort of 10,857 ischemic stroke cases using a linear regression framework. We meta-analyzed all SNPs with p-value < 1×10-5 in a sex-combined or sex-stratified analysis using summary data from two additional replication cohorts. In the women-only meta-analysis, we detected significant evidence for association of AAO with rs429358, an exonic variant in APOE that encodes for the APOE-ϵ4 allele. Each copy of the rs429358:T>C allele was associated with a 1.29 years earlier stroke AOO (meta p-value = 2.48×10-11). This APOE variant has previously been associated with increased mortality and ischemic stroke AAO. We hypothesized that the association with AAO may reflect a survival bias attributable to an age-related decline in mortality among APOE-ϵ4 carriers and have no association to stroke AAO per se. Using a simulation study, we found that a variant associated with overall mortality might indeed be detected with an AAO analysis. A variant with a two-fold increase on mortality risk would lead to an observed effect of AAO that is comparable to what we found. In conclusion, we detected a robust association of the APOE locus with stroke AAO and provided simulations to suggest that this association may be unrelated to ischemic stroke per se but related to a general survival bias.

Genomic risk scores and oral contraceptive-associated ischemic stroke risk: a call for collaboration.

Background: Oral contraceptives (OCs) are generally safe but vascular risk factors increase OC-associated ischemic stroke risk. We performed a case-control study to evaluate whether a genomic risk score for ischemic stroke modifies OC-associated ischemic stroke risk. Methods: The Genetics of Early-Onset Stroke study includes 332 premenopausal women (136 arterial ischemic stroke cases and 196 controls) with data on estrogen-containing OC use within 30 days before the index event (for cases) or interview (for controls). Using a previously validated genetic risk score (metaGRS) for ischemic stroke based on 19 polygenic risk scores for stroke and stroke-associated risk factors, we stratified our combined case-control sample into tertiles of genomic risk. We evaluated the association between OC use and ischemic stroke within each tertile. We tested if the association between OC use and ischemic stroke depended on the genomic risk of stroke using logistic regression with an OC use × metaGRS interaction term. These analyses were performed with and without adjustment for smoking, hypertension, diabetes, coronary heart disease, and body mass index. Results: After adjustment for vascular risk factors, the odds ratio of OC use was 3.2 (1.7-6.3) overall and increased from the lower, middle, and upper tertile of genomic risk from 1.6 (0.5-5.4) to 2.5 (0.08-8.2) to 13.7 (3.8-67.3) respectively, and a p-value for interaction of 0.001. Conclusions: Our results suggest that genomic profile may modify the OC-associated ischemic stroke risk. Larger studies are warranted to determine whether a genomic risk score could be clinically useful in reducing OC-associated ischemic stroke.

Missense variants in SORT1 are associated with LDL-C in an Amish population.

Common noncoding variants at the human 1p13.3 locus associated with SORT1 expression are among those most strongly associated with low-density lipoprotein cholesterol (LDL-C) in human genome-wide association studies. However, validation studies in mice and cell lines have produced variable results regarding the directionality of the effect of SORT1 on LDL-C. This, together with the fact that the 1p13.3 variants are associated with expression of several genes, has raised the question of whether SORT1 is the causal gene at this locus. Using whole exome sequencing in members of an Amish population, we identified coding variants in SORT1 that are associated with increased (rs141749679, K302E) and decreased (rs149456022, Q225H) LDL-C. Further, analysis of plasma lipoprotein particle subclasses by ion mobility in a subset of rs141749679 (K302E) carriers revealed higher levels of large LDL particles compared to noncarriers. In contrast to the effect of these variants in the Amish, the sortilin K302E mutation introduced into a C57BL/6J mouse via CRISPR/Cas9 resulted in decreased non-high-density lipoprotein cholesterol, and the sortilin Q225H mutation did not alter cholesterol levels in mice. This is indicative of different effects of these mutations on cholesterol metabolism in the two species. To our knowledge, this is the first evidence that naturally occurring coding variants in SORT1 are associated with LDL-C, thus supporting SORT1 as the gene responsible for the association of the 1p13.3 locus with LDL-C.

APOE4 poses opposite effects of plasma LDL on white matter integrity in older adults.

INTRODUCTION: APOE4 is a strong genetic risk factor of Alzheimer's disease and is associated with changes in metabolism. However, the interactive relationship between APOE4 and plasma metabolites on the brain remains largely unknown. MEHODS: In the UK Biobank, we investigated the moderation effects of APOE4 on the relationship between 249 plasma metabolites derived from nuclear magnetic resonance spectroscopy on whole-brain white matter integrity, measured by fractional anisotropy using diffusion magnetic resonance imaging. RESULTS: The increase in the concentration of metabolites, mainly LDL and VLDL, is associated with a decrease in white matter integrity (b= -0.12, CI= [-0.14, -0.10]) among older APOE4 carriers, whereas an increase (b= 0.05, CI= [0.04, 0.07]) among non-carriers, implying a significant moderation effect of APOE4 (b= -0.18, CI= [-0.20,-0.15]). DISCUSSION: The results suggest that lipid metabolism functions differently in APOE4 carriers compared to non-carriers, which may inform the development of targeted interventions for APOE4 carriers to mitigate cognitive decline.

A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies.

Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally-scalable analytical pipeline for functionally-informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits (low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides) in 61,861 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered new associations with lipid traits missed by single-trait analysis, including rare variants within an enhancer of NIPSNAP3A and an intergenic region on chromosome 1.

Type 2 Diabetes Modifies the Association of CAD Genomic Risk Variants With Subclinical Atherosclerosis.

BACKGROUND: Individuals with type 2 diabetes (T2D) have an increased risk of coronary artery disease (CAD), but questions remain about the underlying pathology. Identifying which CAD loci are modified by T2D in the development of subclinical atherosclerosis (coronary artery calcification [CAC], carotid intima-media thickness, or carotid plaque) may improve our understanding of the mechanisms leading to the increased CAD in T2D. METHODS: We compared the common and rare variant associations of known CAD loci from the literature on CAC, carotid intima-media thickness, and carotid plaque in up to 29 670 participants, including up to 24 157 normoglycemic controls and 5513 T2D cases leveraging whole-genome sequencing data from the Trans-Omics for Precision Medicine program. We included first-order T2D interaction terms in each model to determine whether CAD loci were modified by T2D. The genetic main and interaction effects were assessed using a joint test to determine whether a CAD variant, or gene-based rare variant set, was associated with the respective subclinical atherosclerosis measures and then further determined whether these loci had a significant interaction test. RESULTS: Using a Bonferroni-corrected significance threshold of P<1.6×10-4, we identified 3 genes (ATP1B1, ARVCF, and LIPG) associated with CAC and 2 genes (ABCG8 and EIF2B2) associated with carotid intima-media thickness and carotid plaque, respectively, through gene-based rare variant set analysis. Both ATP1B1 and ARVCF also had significantly different associations for CAC in T2D cases versus controls. No significant interaction tests were identified through the candidate single-variant analysis. CONCLUSIONS: These results highlight T2D as an important modifier of rare variant associations in CAD loci with CAC.

Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing.

Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fractions and found that individuals of European ancestry have the highest rates of autosomal mCAs and the lowest rates of chromosome X mCAs, compared with individuals of African or Hispanic ancestry. Although further studies in diverse populations will be needed to replicate our findings, we report three loci associated with loss of chromosome X, associations between autosomal mCAs and rare variants in DCPS, ADM17, PPP1R16B and TET2 and ancestry-specific variants in ATM and MPL with mCAs in cis.

Determinants of mosaic chromosomal alteration fitness.

Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well-understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our estimates of mCA fitness were correlated (R 2 = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using a theoretical probability distribution. Individuals with lymphoid-associated mCAs had a significantly higher white blood cell count and faster clonal expansion rate. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified TCL1A , NRIP1 , and TERT locus variants as modulators of mCA clonal expansion rate.

Acute pharmacodynamic responses to sitagliptin: Drug-induced increase in early insulin secretion in oral glucose tolerance test.

Aim: DPP4 inhibitors are widely prescribed as treatments for type 2 diabetes. Because drug responses vary among individuals, we initiated investigations to identify genetic variants associated with the magnitude of drug responses. Methods: Sitagliptin (100 mg) was administered to 47 healthy volunteers. Several endpoints were measured to assess clinically relevant responses - including the effect of sitagliptin on glucose and insulin levels during an oral glucose tolerance test (OGTT). Results: This pilot study confirmed that sitagliptin (100 mg) decreased the area under the curve for glucose during an OGTT (p=0.0003). Furthermore, sitagliptin promoted insulin secretion during the early portion of the OGTT as reflected by an increase in the ratio of plasma insulin at 30 min divided by plasma insulin at 60 min (T30:T60) from 0.87+/-0.05 to 1.62+/-0.36 mU/L (p=0.04). The magnitude of sitagliptin's effect on insulin secretion (as judged by the increase in the T30:T60 ratio for insulin) was correlated with the magnitude of sitagliptin-induced increase in the area under the curve for intact plasma GLP1 levels during the first hour of the OGTT. This study confirmed previously reported sex differences in glucose and insulin levels during an OGTT. Specifically, females exhibited higher levels of glucose and insulin at the 90-180 min time points. However, we did not detect significant sex-associated differences in the magnitude of sitagliptin-induced changes in T30:T60 ratios for either glucose or insulin. Conclusions: T30:T60 ratios for insulin and glucose during an OGTT provide useful indices to assess pharmacodynamic responses to DPP4 inhibitors.

Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study.

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs.

Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium.

Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.

Elevated blood pressure accelerates white matter brain aging among late middle-aged women: a Mendelian Randomization study in the UK Biobank.

BACKGROUND: Elevated blood pressure (BP) is a modifiable risk factor associated with cognitive impairment and cerebrovascular diseases. However, the causal effect of BP on white matter brain aging remains unclear. METHODS: In this study, we focused on N  = 228 473 individuals of European ancestry who had genotype data and clinical BP measurements available (103 929 men and 124 544 women, mean age = 56.49, including 16 901 participants with neuroimaging data available) collected from UK Biobank (UKB). We first established a machine learning model to compute the outcome variable brain age gap (BAG) based on white matter microstructure integrity measured by fractional anisotropy derived from diffusion tensor imaging data. We then performed a two-sample Mendelian randomization analysis to estimate the causal effect of BP on white matter BAG in the whole population and subgroups stratified by sex and age brackets using two nonoverlapping data sets. RESULTS: The hypertension group is on average 0.31 years (95% CI = 0.13-0.49; P  < 0.0001) older in white matter brain age than the nonhypertension group. Women are on average 0.81 years (95% CI = 0.68-0.95; P  < 0.0001) younger in white matter brain age than men. The Mendelian randomization analyses showed an overall significant positive causal effect of DBP on white matter BAG (0.37 years/10 mmHg, 95% CI 0.034-0.71, P  = 0.0311). In stratified analysis, the causal effect was found most prominent among women aged 50-59 and aged 60-69. CONCLUSION: High BP can accelerate white matter brain aging among late middle-aged women, providing insights on planning effective control of BP for women in this age group.

Carriers of rare damaging CCR2 genetic variants are at lower risk of atherosclerotic disease.

Background: The CCL2/CCR2 axis governs monocyte trafficking and recruitment to atherosclerotic lesions. Human genetic analyses and population-based studies support an association between circulating CCL2 levels and atherosclerosis. Still, it remains unknown whether pharmacological targeting of CCR2, the main CCL2 receptor, would provide protection against human atherosclerotic disease. Methods: In whole-exome sequencing data from 454,775 UK Biobank participants (40-69 years), we identified predicted loss-of-function (LoF) or damaging missense (REVEL score >0.5) variants within the CCR2 gene. We prioritized variants associated with lower monocyte count (p<0.05) and tested associations with vascular risk factors and risk of atherosclerotic disease over a mean follow-up of 14 years. The results were replicated in a pooled cohort of three independent datasets (TOPMed, deCODE and Penn Medicine BioBank; total n=441,445) and the effect of the most frequent damaging variant was experimentally validated. Results: A total of 45 predicted LoF or damaging missense variants were identified in the CCR2 gene, 4 of which were also significantly associated with lower monocyte count, but not with other white blood cell counts. Heterozygous carriers of these variants were at a lower risk of a combined atherosclerosis outcome, showed a lower burden of atherosclerosis across four vascular beds, and were at a lower lifetime risk of coronary artery disease and myocardial infarction. There was no evidence of association with vascular risk factors including LDL-cholesterol, blood pressure, glycemic status, or C-reactive protein. Using a cAMP assay, we found that cells transfected with the most frequent CCR2 damaging variant (3:46358273:T:A, M249K, 547 carriers, frequency: 0.14%) show a decrease in signaling in response to CCL2. The associations of the M249K variant with myocardial infarction were consistent across cohorts (ORUKB: 0.62 95%CI: 0.39-0.96; ORexternal: 0.64 95%CI: 0.34-1.19; ORpooled: 0.64 95%CI: 0.450.90). In a phenome-wide association study, we found no evidence for higher risk of common infections or mortality among carriers of damaging CCR2 variants. Conclusions: Heterozygous carriers of damaging CCR2 variants have a lower burden of atherosclerosis and lower lifetime risk of myocardial infarction. In conjunction with previous evidence from experimental and epidemiological studies, our findings highlight the translational potential of CCR2-targeting as an atheroprotective approach.