Dr. Clarke is a preventive cardiologist and an instructor at Stanford University School of Medicine in the Departments of Medicine and Pediatrics. He earned his undergraduate degree in human biology from the Division of Nutritional Sciences at Cornell University before obtaining his MD and PhD (genetics) from Stanford University School of Medicine. He has completed clinical training in internal medicine (Brigham & Women’s Hospital), pediatrics (Boston Children’s Hospital), and cardiovascular medicine (Stanford Hospital), and he is board certified in all three specialties. His research is focused on 1) understanding complex disease genetics in diverse populations, 2) integrating monogenic and polygenic risk with clinical risk, 3) large-scale phenotyping using the electronic health record. His clinical practice focuses on identifying risk factors for cardiovascular disease with the goal of promoting health and longevity through evidence-based personalized treatment. He is interested in developing family-centric approaches for the treatment of adults and children carrying high genetic risk for disease.
- Preventive Cardiology
- Familial Hypercholesterolemia
- Coronary Artery Disease
- Coronary Artery Calcification
- Internal Medicine
Instructor, Pediatrics - Cardiology
Honors & Awards
Chair Diversity Investigator Award, Stanford University Department of Medicine (2021)
Chief Fellow, Stanford Division of Cardiovascular Medicine (2019)
House Officer Research Award, Boston Children's Hospital (2016)
Gilliam Fellow, Howard Hughes Medical Institute (2008 - 2013)
Board Certification: American Board of Internal Medicine, Cardiovascular Disease (2020)
Board certified, American Board of Internal Medicine, Cardiovascular Disease
Board certified, American Board of Pediatrics, Pediatrics
Board certified, American Board of Internal Medicine, Internal Medicine
Fellow, Stanford University School of Medicine, Cardiovascular Medicine (2020)
Resident, Brigham & Women's Hospital and Boston Children's Hospital, Internal Medicine and Pediatrics (2017)
PhD, Stanford University School of Medicine, Genetics (2013)
MD, Stanford University School of Medicine (2013)
- Time to Relax the 40-Year Age Threshold for Pharmacologic Cholesterol Lowering. Journal of the American College of Cardiology 2021; 78 (20): 1965-1967
The Propagation of Racial Disparities in Cardiovascular Genomics Research.
Circulation. Genomic and precision medicine
Genomics research has improved our understanding of the genetic basis for human traits and diseases. This progress is now being translated into clinical care as we move toward a future of precision medicine. Many hope that expanded use of genomic testing will improve disease screening, diagnosis, risk stratification, and treatment. In many respects, cardiovascular medicine is leading this charge. However, most cardiovascular genomics research has been conducted in populations of primarily European ancestry. This bias has critical downstream effects. Here, we review the current disparities in cardiovascular genomics research, and we outline how these disparities propagate forward through all phases of the translational pipeline. If not adequately addressed, biases in genomics research will further compound the existing health disparities that face underrepresented and marginalized populations.
View details for DOI 10.1161/CIRCGEN.121.003178
View details for PubMedID 34461749
Associations of Genetically Predicted Lipoprotein (a) Levels with Cardiovascular Traits in Individuals of European and African Ancestry.
Circulation. Genomic and precision medicine
Background - Lipoprotein (a) [Lp(a)] levels are higher in individuals of African ancestry (AA) than in individuals of European ancestry (EA). We examined associations of genetically predicted Lp(a) levels with 1) atherosclerotic cardiovascular disease (ASCVD) subtypes: coronary heart disease (CHD), cerebrovascular disease (CVD), peripheral artery disease (PAD), and abdominal aortic aneurysm (AAA); and 2) non-ASCVD phenotypes, stratified by ancestry. Methods - We performed 1) Mendelian randomization (MR) analyses for previously reported cardiovascular associations, and 2) phenome-wide MR (MR-PheWAS) analyses for novel associations. Analyses were stratified by ancestry in electronic MEdical Records and GEnomics, United Kingdom Biobank, and Million Veteran Program cohorts separately and in a combined cohort of 804,507 EA and 103,580 AA participants. Results - In MR analyses using the combined cohort, a 1-standard deviation (SD) genetic increase in Lp(a) level was associated with ASCVD subtypes in EA - odds ratio and 95% confidence interval for CHD 1.28(1.16-1.41); CVD 1.14(1.07-1.21); PAD 1.22(1.11-1.34); AAA 1.28(1.17-1.40); in AA the effect estimate was lower than in EA and nonsignificant for CHD 1.11(0.99-1.24) and CVD 1.06(0.99-1.14) but similar for PAD 1.16(1.01-1.33) and AAA 1.34(1.11-1.62). In EA, a 1-SD genetic increase in Lp(a) level was associated with aortic valve disorders 1.34(1.10-1.62), mitral valve disorders 1.18(1.09-1.27), congestive heart failure 1.12(1.05-1.19), and chronic kidney disease 1.07(1.01-1.14). In AA no significant associations were noted for aortic valve disorders 1.08(0.94-1.25), mitral valve disorders 1.02(0.89-1.16), congestive heart failure 1.02(0.95-1.10), or chronic kidney disease 1.05(0.99-1.12). MR-PheWAS identified novel associations in EA with arterial thromboembolic disease, non-aortic aneurysmal disease, atrial fibrillation, cardiac conduction disorders, and hypertension. Conclusions - Many cardiovascular associations of genetically increased Lp(a) that were significant in EA were not significant in AA. Lp(a) was associated with ASCVD in four major arterial beds in EA but only with PAD and AAA in AA. Additional, novel cardiovascular associations were detected in EA.
View details for DOI 10.1161/CIRCGEN.120.003354
View details for PubMedID 34282949
BROAD CLINICAL MANIFESTATIONS OF POLYGENIC RISK FOR CORONARY ARTERY DISEASE IN THE WOMEN'S HEALTH INITIATIVE
ELSEVIER SCIENCE INC. 2021: 1511
View details for Web of Science ID 000647487501519
Validation of an Integrated Risk Tool, Including Polygenic Risk Score, for Atherosclerotic Cardiovascular Disease in Multiple Ethnicities and Ancestries.
The American journal of cardiology
The American College of Cardiology / American Heart Association pooled cohort equations tool (ASCVD-PCE) is currently recommended to assess 10-year risk for atherosclerotic cardiovascular disease (ASCVD). ASCVD-PCE does not currently include genetic risk factors. Polygenic risk scores (PRSs) have been shown to offer a powerful new approach to measuring genetic risk for common diseases, including ASCVD, and to enhance risk prediction when combined with ASCVD-PCE. Most work to date, including the assessment of tools, has focused on performance in individuals of European ancestries. Here we present evidence for the clinical validation of a new integrated risk tool (IRT), ASCVD-IRT, which combines ASCVD-PCE with PRS to predict 10-year risk of ASCVD across diverse ethnicity and ancestry groups. We demonstrate improved predictive performance of ASCVD-IRT over ASCVD-PCE, not only in individuals of self-reported White ethnicities (net reclassification improvement (NRI) (with 95% confidence interval) = 2.7% (1.1 - 4.2)) but also Black / African American / Black Caribbean / Black African (NRI = 2.5% (0.6 - 4.3)) and South Asian (Indian, Bangladeshi or Pakistani) ethnicities (NRI = 8.7% (3.1 - 14.4)). NRI confidence intervals were wider and included zero for ethnicities with smaller sample sizes, including Hispanic (NRI = 7.5% (-1.4 - 16.5)), but PRS effect sizes in these ethnicities were significant and of comparable size to those seen in individuals of White ethnicities. Comparable results were obtained when individuals were analysed by genetically inferred ancestry. Together, these results validate the performance of ASCVD-IRT in multiple ethnicities and ancestries, and favour their generalisation to all ethnicities and ancestries.
View details for DOI 10.1016/j.amjcard.2021.02.032
View details for PubMedID 33675770
The need for polygenic score reporting standards in evidence-based practice: lipid genetics use case.
Current opinion in lipidology
Polygenic scores (PGS) are used to quantify the genetic predisposition for heritable traits, with hypothesized utility for personalized risk assessments. Lipid PGS are primed for clinical translation, but evidence-based practice changes will require rigorous PGS standards to ensure reproducibility and generalizability. Here we review applicable reporting and technical standards for dyslipidemia PGS translation along phases of the ACCE (Analytical validity, Clinical validity, Clinical utility, Ethical considerations) framework for evaluating genetic tests.New guidance suggests existing standards for study designs incorporating the ACCE framework are applicable to PGS and should be adopted. One recent example is the Clinical Genomics Resource (ClinGen) and Polygenic Score Catalog's PRS reporting standards, which define minimal requirements for describing rationale for score development, study population definitions and data parameters, risk model development and application, risk model evaluation, and translational considerations, such as generalizability beyond the target population studied.Lipid PGS are likely to be integrated into clinical practice in the future. Clinicians will need to be prepared to determine if and when lipid PGS is useful and valid. This decision-making will depend on the quality of evidence for the clinical use of PGS. Establishing reporting standards for PGS will help facilitate data sharing and transparency for critical evaluation, ultimately benefiting the efficiency of evidence-based practice.
View details for DOI 10.1097/MOL.0000000000000733
View details for PubMedID 33538426
Combining Clinical and Polygenic Risk Improves Stroke Prediction Among Individuals with Atrial Fibrillation.
Circulation. Genomic and precision medicine
Background - Atrial fibrillation (AF) is associated with a five-fold increased risk of ischemic stroke. A portion of this risk is heritable, however current risk stratification tools (CHA2DS2-VASc) don't include family history or genetic risk. We hypothesized that we could improve ischemic stroke prediction in patients with AF by incorporating polygenic risk scores (PRS). Methods - Using data from the largest available GWAS in Europeans, we combined over half a million genetic variants to construct a PRS to predict ischemic stroke in patients with AF. We externally validated this PRS in independent data from the UK Biobank, both independently and integrated with clinical risk factors. The integrated PRS and clinical risk factors risk tool had the greatest predictive ability. Results - Compared with the currently recommended risk tool (CHA2DS2-VASc), the integrated tool significantly improved net reclassification (NRI: 2.3% (95%CI: 1.3% to 3.0%)), and fit (χ2 P =0.002). Using this improved tool, >115,000 people with AF would have improved risk classification in the US. Independently, PRS was a significant predictor of ischemic stroke in patients with AF prospectively (Hazard Ratio: 1.13 per 1 SD (95%CI: 1.06 to 1.23)). Lastly, polygenic risk scores were uncorrelated with clinical risk factors (Pearson's correlation coefficient: -0.018). Conclusions - In patients with AF, there appears to be a significant association between PRS and risk of ischemic stroke. The greatest predictive ability was found with the integration of PRS and clinical risk factors, however the prediction of stroke remains challenging.
View details for DOI 10.1161/CIRCGEN.120.003168
View details for PubMedID 34029116
- A New Era for Preventive Cardiology. Trends in cardiovascular medicine 2021
Combining Clinical and Polygenic Risk Improves Stroke Prediction Among Individuals With Atrial Fibrillation
LIPPINCOTT WILLIAMS & WILKINS. 2020
View details for Web of Science ID 000607190401150
- Risk of Coronary Artery Disease Associated With Familial Hypercholesterolemia Genetic Variants is Independent of Historical Low-density Lipoprotein Cholesterol Exposure LIPPINCOTT WILLIAMS & WILKINS. 2020
LPA Variants Are Associated With Aortic Valve Stenosis, Heart Failure and Chronic Kidney Disease
LIPPINCOTT WILLIAMS & WILKINS. 2020
View details for Web of Science ID 000607190403040
Cardiorespiratory Fitness, Body-Mass Index, and Markers of Insulin Resistance in Apparently Healthy Women and Men.
The American journal of medicine
BACKGROUND: Insulin resistance may be present in healthy adults and is associated poor health outcomes. Obesity is a risk factor for insulin resistance, but most obese adults do not have insulin resistance. Fitness may be protective, but the association between fitness, weight, and insulin resistance has not been studied in a large population of healthy adults.METHODS: A cross-sectional analysis of cardiorespiratory fitness, body-mass index, and markers of insulin resistance was performed. Study participants were enrolled at the Cooper Clinic (Dallas, Texas). The analysis included 19,263 women and 48,433 men with no history of diabetes or cardiovascular disease. Cardiorespiratory fitness was measured using exercise treadmill testing. Impaired fasting glucose (100-125 mg/dL) and elevated fasting triglycerides (≥150 mg/dL) were used as a markers of insulin resistance.RESULTS: Among normal weight individuals, poor fitness was associated with a 2.2 (1.4-3.6; p=0.001) fold higher odds of insulin resistance in women and a 2.8 (2.1-3.6; p<0.001) fold higher odds in men. The impact of fitness remained significant for overweight and obese individuals, with the highest risk group being the unfit obese. Among obese women, the odds ratio for insulin resistance was 11.0 (8.7-13.9; p<0.001) for fit and 20.3 (15.5-26.5; p<0.001) for unfit women. Among obese men, the odds ratio for insulin resistance was 7.4 (6.7-8.2; p<0.001) for fit and 12.9 (11.4-14.6; p<0.001) for unfit men.CONCLUSION: Independent of weight, poor fitness is associated with risk of insulin resistance. Obese individuals, particularly women, may benefit from the greatest absolute risk reduction by achieving moderate fitness.
View details for DOI 10.1016/j.amjmed.2019.11.031
View details for PubMedID 31926863
- Performance of Polygenic Risk Scores for Coronary Artery Disease in the Million Veteran Program LIPPINCOTT WILLIAMS & WILKINS. 2019
Genome-Wide Association Studies of Coronary Artery Disease: Recent Progress and Challenges Ahead.
Current atherosclerosis reports
2018; 20 (9): 47
Genome-wide association studies (GWAS) have been the primary tool for unbiased assessment of the genetic basis of coronary artery disease (CAD) for more than a decade. We summarize successes as well as shortcomings of recent studies in this context.The number of CAD-associated loci has more than doubled in the past year to 161. This rapid progress has been in large part due to the release of genome-wide genotyping data for the largely European participants of the UK Biobank study which has been combined with existing GWAS from the CARDIoGRAMplusC4D consortium. Additional discoveries have been achieved through large-scale genotyping of participants using custom high-yield genotyping arrays including the Metabochip and the Exome chip. As a consequence, the ability of genetic risk scores in predicting incident CAD events has improved but that improvement has only been shown in European populations. GWAS have proven to be a fruitful approach for uncovering the genetic drivers of CAD. However, determining the mechanisms of association of GWAS findings remains a challenging endeavor requiring long-term investment. Genetic risk scores offer an opportunity for recent findings to have an immediate clinical impact. Going forward, CAD genetics will benefit greatly from the release of more genetic data produced by mega-biobanks. These new data will allow for the more comprehensive examination of underrepresented populations.
View details for DOI 10.1007/s11883-018-0748-4
View details for PubMedID 30022313
Erosion of Conserved Binding Sites in Personal Genomes Points to Medical Histories.
PLoS computational biology
2016; 12 (2)
Although many human diseases have a genetic component involving many loci, the majority of studies are statistically underpowered to isolate the many contributing variants, raising the question of the existence of alternate processes to identify disease mutations. To address this question, we collect ancestral transcription factor binding sites disrupted by an individual's variants and then look for their most significant congregation next to a group of functionally related genes. Strikingly, when the method is applied to five different full human genomes, the top enriched function for each is invariably reflective of their very different medical histories. For example, our method implicates "abnormal cardiac output" for a patient with a longstanding family history of heart disease, "decreased circulating sodium level" for an individual with hypertension, and other biologically appealing links for medical histories spanning narcolepsy to axonal neuropathy. Our results suggest that erosion of gene regulation by mutation load significantly contributes to observed heritable phenotypes that manifest in the medical history. The test we developed exposes a hitherto hidden layer of personal variants that promise to shed new light on human disease penetrance, expressivity and the sensitivity with which we can detect them.
View details for DOI 10.1371/journal.pcbi.1004711
View details for PubMedID 26845687
View details for PubMedCentralID PMC4742230
The enhancer landscape during early neocortical development reveals patterns of dense regulation and co-option.
2013; 9 (8)
Genetic studies have identified a core set of transcription factors and target genes that control the development of the neocortex, the region of the human brain responsible for higher cognition. The specific regulatory interactions between these factors, many key upstream and downstream genes, and the enhancers that mediate all these interactions remain mostly uncharacterized. We perform p300 ChIP-seq to identify over 6,600 candidate enhancers active in the dorsal cerebral wall of embryonic day 14.5 (E14.5) mice. Over 95% of the peaks we measure are conserved to human. Eight of ten (80%) candidates tested using mouse transgenesis drive activity in restricted laminar patterns within the neocortex. GREAT based computational analysis reveals highly significant correlation with genes expressed at E14.5 in key areas for neocortex development, and allows the grouping of enhancers by known biological functions and pathways for further studies. We find that multiple genes are flanked by dozens of candidate enhancers each, including well-known key neocortical genes as well as suspected and novel genes. Nearly a quarter of our candidate enhancers are conserved well beyond mammals. Human and zebrafish regions orthologous to our candidate enhancers are shown to most often function in other aspects of central nervous system development. Finally, we find strong evidence that specific interspersed repeat families have contributed potentially key developmental enhancers via co-option. Our analysis expands the methodologies available for extracting the richness of information found in genome-wide functional maps.
View details for DOI 10.1371/journal.pgen.1003728
View details for PubMedID 24009522
View details for PubMedCentralID PMC3757057
PRISM offers a comprehensive genomic approach to transcription factor function prediction.
2013; 23 (5): 889-904
The human genome encodes 1500-2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells.
View details for DOI 10.1101/gr.139071.112
View details for PubMedID 23382538
View details for PubMedCentralID PMC3638144
Human Developmental Enhancers Conserved between Deuterostomes and Protostomes
2012; 8 (8)
The identification of homologies, whether morphological, molecular, or genetic, is fundamental to our understanding of common biological principles. Homologies bridging the great divide between deuterostomes and protostomes have served as the basis for current models of animal evolution and development. It is now appreciated that these two clades share a common developmental toolkit consisting of conserved transcription factors and signaling pathways. These patterning genes sometimes show common expression patterns and genetic interactions, suggesting the existence of similar or even conserved regulatory apparatus. However, previous studies have found no regulatory sequence conserved between deuterostomes and protostomes. Here we describe the first such enhancers, which we call bilaterian conserved regulatory elements (Bicores). Bicores show conservation of sequence and gene synteny. Sequence conservation of Bicores reflects conserved patterns of transcription factor binding sites. We predict that Bicores act as response elements to signaling pathways, and we show that Bicores are developmental enhancers that drive expression of transcriptional repressors in the vertebrate central nervous system. Although the small number of identified Bicores suggests extensive rewiring of cis-regulation between the protostome and deuterostome clades, additional Bicores may be revealed as our understanding of cis-regulatory logic and sample of bilaterian genomes continue to grow.
View details for DOI 10.1371/journal.pgen.1002852
View details for Web of Science ID 000308529300014
View details for PubMedID 22876195
View details for PubMedCentralID PMC3410860
Coding exons function as tissue-specific enhancers of nearby genes
2012; 22 (6): 1059-1068
Enhancers are essential gene regulatory elements whose alteration can lead to morphological differences between species, developmental abnormalities, and human disease. Current strategies to identify enhancers focus primarily on noncoding sequences and tend to exclude protein coding sequences. Here, we analyzed 25 available ChIP-seq data sets that identify enhancers in an unbiased manner (H3K4me1, H3K27ac, and EP300) for peaks that overlap exons. We find that, on average, 7% of all ChIP-seq peaks overlap coding exons (after excluding for peaks that overlap with first exons). By using mouse and zebrafish enhancer assays, we demonstrate that several of these exonic enhancer (eExons) candidates can function as enhancers of their neighboring genes and that the exonic sequence is necessary for enhancer activity. Using ChIP, 3C, and DNA FISH, we further show that one of these exonic limb enhancers, Dync1i1 exon 15, has active enhancer marks and physically interacts with Dlx5/6 promoter regions 900 kb away. In addition, its removal by chromosomal abnormalities in humans could cause split hand and foot malformation 1 (SHFM1), a disorder associated with DLX5/6. These results demonstrate that DNA sequences can have a dual function, operating as coding exons in one tissue and enhancers of nearby gene(s) in another tissue, suggesting that phenotypes resulting from coding mutations could be caused not only by protein alteration but also by disrupting the regulation of another gene.
View details for DOI 10.1101/gr.133546.111
View details for Web of Science ID 000304728100007
View details for PubMedID 22442009
View details for PubMedCentralID PMC3371700
Control of Pelvic Girdle Development by Genes of the Pbx Family and Emx2
2011; 240 (5): 1173-1189
Genes expressed in the somatopleuric mesoderm, the embryonic domain giving rise to the vertebrate pelvis, appear important for pelvic girdle formation. Among such genes, Pbx family members and Emx2 were found to genetically interact in hindlimb and pectoral girdle formation. Here, we generated compound mutant embryos carrying combinations of mutated alleles for Pbx1, Pbx2, and Pbx3, as well as Pbx1 and Emx2, to examine potential genetic interactions during pelvic development. Indeed, Pbx genes share overlapping functions and Pbx1 and Emx2 genetically interact in pelvic formation. We show that, in compound Pbx1;Pbx2 and Pbx1;Emx2 mutants, pelvic mesenchymal condensation is markedly perturbed, indicative of an upstream control by these homeoproteins. We establish that expression of Tbx15, Prrx1, and Pax1, among other genes involved in the specification and development of select pelvic structures, is altered in our compound mutants. Lastly, we identify potential Pbx1-Emx2-regulated enhancers for Tbx15, Prrx1, and Pax1, using bioinformatics analyses.
View details for DOI 10.1002/dvdy.22617
View details for Web of Science ID 000289942300023
View details for PubMedID 21455939
View details for PubMedCentralID PMC3081414
GREAT improves functional interpretation of cis-regulatory regions
2010; 28 (5): 495-U155
We developed the Genomic Regions Enrichment of Annotations Tool (GREAT) to analyze the functional significance of cis-regulatory regions identified by localized measurements of DNA binding events across an entire genome. Whereas previous methods took into account only binding proximal to genes, GREAT is able to properly incorporate distal binding sites and control for false positives using a binomial test over the input genomic regions. GREAT incorporates annotations from 20 ontologies and is available as a web application. Applying GREAT to data sets from chromatin immunoprecipitation coupled with massively parallel sequencing (ChIP-seq) of multiple transcription-associated factors, including SRF, NRSF, GABP, Stat3 and p300 in different developmental contexts, we recover many functions of these factors that are missed by existing gene-based tools, and we generate testable hypotheses. The utility of GREAT is not limited to ChIP-seq, as it could also be applied to open chromatin, localized epigenomic markers and similar functional data sets, as well as comparative genomics sets.
View details for DOI 10.1038/nbt.1630
View details for Web of Science ID 000277452700030
View details for PubMedID 20436461