About

Clay Anderson is a professor at MIT's Department of Urban Studies and Planning (DUSP). His research focuses on urban planning, transportation policy, and sustainable urban development. As a faculty member, he contributes to the academic community through teaching and research, engaging with issues related to urban design, mobility, and city development. His work supports the advancement of sustainable and equitable urban environments, leveraging his expertise to influence urban policy and planning practices.

Research topics

• Medicine
• Computer Science
• Genetics
• Biology
• Classics
• Surgery
• Evolutionary biology
• Bioinformatics
• Library science
• Demography
• History

Selected publications

• PD15-14 THE COST OF ACTIVE SURVEILLANCE IN MUSCLE-INVASIVE BLADDER CANCER FOR CLINICAL COMPLETE RESPONSE TO NEOADJUVANT SYSTEMIC THERAPY

  The Journal of Urology · 2026-04-27

  article
  PublisherDOI

• IP50-20 SANCTUARY SITE EVALUATION IN PATIENTS WITH BCG-UNRESPONSIVE NON-MUSCLE INVASIVE BLADDER CANCER

  The Journal of Urology · 2026-04-27

  article
  PublisherDOI

• The Ethnic/Racial Variations of Intracerebral Hemorrhage Genetics (ERICH-GENE) Study Protocol

  medRxiv · 2025-06-13 · 1 citations

  preprintOpen access

  Background: Spontaneous, non-traumatic intracranial hemorrhage (ICH) is highly heritable disease. However, the identification of the genetic risk factors driving this high genetic predisposition has been limited by small sample sizes and underrepresentation of non-European populations. The ERICH-GENE study will gather and harmonize clinical, neuroimaging and genomic data on the largest and more diverse collection of ICH cases assembled to date. Methods: ERICH-GENE is an NIH-funded, multi-center, international, genetic and neuroimaging study that aims to achieve the necessary sample size and diversity required to accurately describe the genetic architecture and trans-ethnic variation of ICH. ERICH-GENE will collect and harmonize clinical, neuroimaging and genomic data at least 10,000 multi-ethnic ICH cases. These data will be aggregated with 20,000 existing ICH cases and 600,000 ICH-free controls available through completed studies by the International Stroke Genetics Consortium. To ensure validity, data will undergo extensive harmonization, including expert review of neuroimages to ensure spontaneous etiology and hemorrhage location. We will conduct genome-wide association studies of risk, severity and outcome of ICH, testing for effect modification by race/ethnicity, sex and hemorrhage location. We will also conduct pathway, polygenic risk score and Mendelian randomization analyses. Results: This study will include whole genome sequencing data from 10,850 spontaneous ICH samples, including clinical and radiographic phenotypic data to ensure reliability of true non-traumatic, non-lesional ICH and lobar vs nonlobar location. Of these, 1,497 have already been genotyped using genome-wide arrays, 3,753 have undergone whole genome sequencing, and 5,600 will undergo genome-wide genotyping through ERICH-GENE. There are currently 42 contributing sites exceeding study milestone enrollments. 16,175 radiographic studies from 4,974 patients have been uploaded for harmonization to date, including 26% lobar and 64% nonlobar hemorrhages. Neuroimaging assessment will also include grading for white matter hyperintensities, cerebral atrophy, and presence and severity of IVH. Nearly 6,000 ICH cases will complete genotyping by August 2025. Data/material transfer agreements for summary statistics as well as additional samples are on target to meet the study's objectives. Conclusion: ERICH-GENE is the largest trans-ethnic genetic study of ICH conducted to date. Combining a diverse patient population with expert adjudication of neuroimaging data, ERICH-GENE will identify genetic risk loci that drive the high heritability observed for this disease and make a significant contribution to the understanding of the trans-ethnic variation of its genetic architecture.

  PublisherOA PDFDOI

• Association of Plasma GFAP and NfL in Middle-Aged Adults With MRI Markers of Cerebral Small Vessel Disease Later in Life

  Neurology · 2025-12-29

  articleSenior author

  BACKGROUND AND OBJECTIVES: Cerebral small vessel disease (cSVD) is a major contributor to stroke and dementia, often beginning decades before clinical symptoms appear. While MRI markers offer critical insight into cSVD burden, blood-based biomarkers may offer a more accessible complement to neuroimaging. We investigated whether plasma glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are associated with MRI markers of cSVD in middle-aged adults and whether they are associated with longitudinal progression. METHODS: We conducted a retrospective analysis of prospectively collected data from the UK Biobank cohort. Participants aged 40-60 years at baseline (2006-2010) with plasma biomarker measurements and follow-up MRI scans (2014-2019) were included. Individuals with prevalent neurologic conditions were excluded. We assessed 3 MRI markers of cSVD: white matter hyperintensities (WMHs), fractional anisotropy (FA), and mean diffusivity (MD). Three analytical approaches were used: associations between baseline biomarkers and future MRI markers, associations between baseline biomarkers and longitudinal MRI changes, and correlations between longitudinal biomarker and MRI changes. Robust regression models were adjusted for age, sex, and cerebrovascular risk factors. RESULTS: = 0.025) over 3 years. NfL was not significantly associated with any MRI cSVD marker. Longitudinal changes in both biomarkers showed no significant associations with concurrent MRI progression. DISCUSSION: Plasma GFAP levels were associated with subsequent changes in white matter integrity among middle-aged adults, suggesting potential utility as an early indicator of cSVD vulnerability. These associations, observed nearly a decade after biomarker measurement, highlight GFAP's potential for long-term risk stratification. Blood-based biomarkers may support earlier identification of individuals at heightened risk of cSVD, enabling preventive strategies when interventions may be most effective.

  PublisherDOI

• Influence of Ancestral and Geographic Factors on Intracerebral Hemorrhage Risks Among Africans and Americans

  Stroke · 2025-09-24

  article

  BACKGROUND: We investigated whether risk factors for intracerebral hemorrhage (ICH) among indigenous Africans (IA) would vary in prevalence and effect compared with self-reported African, Hispanic, and White Americans by comparing data from 2 independent population-based case-control studies conducted in West Africa and the United States. METHODS: We compared ICH risk factors common to the SIREN (Stroke Investigative Research and Educational Network: 1100 case-control pairs) and the ERICH (Ethnic/Racial Variation of Intracerebral Hemorrhage: 999 case-control pairs African American participants, 998 case-control pairs, Hispanic Americans, 1000 case-control pairs, White Americans) studies. Ethnicity/Race was self-reported. The effect measure of interest is the odds ratio (OR). To test for differences in the effects of the risk factors between the SIREN IA study population and each of the ERICH study populations, a test for heterogeneity was computed using the R program, metagen (version 4.9-6). RESULTS: ICH occurred at a younger age among IA (54.3±13.4 years), African Americans (58.0±12.7), and Hispanic Americans (58.9±14.3), compared with White Americans (69.1±13.9). The largest distinction was for hypertension, where IA exhibited a much larger risk of ICH than the American study population (OR, 67.02 [95% CI, 33.30-134.85]), African American (OR, 3.71 [95% CI, 2.53-5.44]); Hispanic (OR, 3.55 [95% CI, 2.54-4.92]), and White population (OR, 2.69 [95% CI, 1.95-3.69]). Current alcohol use exhibited increased risk in IA (OR, 2.24 [95% CI, 1.36-3.67]), but not in African Americans (OR, 0.63 [95% CI, 0.46-0.86]), Hispanic (OR, 0.87 [95% CI, 0.65-1.17]), and White Americans (OR, 0.51 [95% CI, 0.38-0.69]). CONCLUSIONS: Identical or comparable risk factors do not consistently result in the same disease risk across different cultures and regions. Therefore, to improve our understanding of the genetic determinants and biological pathways driving ICH risk, it is crucial to study multiple populations, including IA, while accounting for the influence of environmental and social factors.

  PublisherDOI

• A rare case of inflammatory myofibroblastic tumour mimicking retained prostatic tissue following HoLEP

  Urology Case Reports · 2025-07-21

  articleOpen access

  Retained prostatic tissue following HoLEP is rare but requires prompt surgical intervention. We present the case of rapidly growing inflammatory myofibroblastic tumour of the bladder presenting shortly after HoLEP, successfully resected in an en-bloc fashion with Holmium-YAG laser. Further prospective data is required for genitourinary inflammatory myofibroblastic tumours to standardise oncological management.

  PublisherDOI

• Abstract 4366460: Atrial Fibrillation Risk Estimated Using Electrocardiogram-based Artificial Intelligence Stratifies Incidence of Atrial Fibrillation-Related Stroke and Heart Failure

  Circulation · 2025-11-03

  article

  Background: Risk of future atrial fibrillation (AF) can be estimated using artificial intelligence (AI)-enabled electrocardiogram (ECG) analysis. However, it remains unknown whether such models may also enrich for risk of potentially preventable AF-related adverse outcomes (e.g., stroke, heart failure [HF]). Hypothesis: We hypothesized that AF risk estimates derived from a validated ECG-based AI model would also associate with future incidence of stroke and HF. Methods: Among primary care and cardiology patients at two institutions (Massachusetts General Hospital [MGH] and Brigham and Women's Hospital [BWH]) separate from model development, we estimated 5-year AF risk using ECG-AI, a previously validated ECG-based deep learning model developed to predict future AF risk. We assessed associations between estimated AF risk and incident AF, stroke, and HF using Cox proportional hazards models adjusted for age and sex. We fit analogous models for AF-related stroke and HF, defined as incident stroke or HF in which AF occurred either before the event or within 30 days after the event. Individuals with either AF or the target outcome at baseline were excluded. Event discrimination was quantified using the area under the time-dependent receiver operating characteristic curves (AUROC) at 5 years. Cumulative risk of events was plotted across tertiles of ECG-AI risk score. Results: We identified 15,269 patients from MGH (mean age 56.5±16.6 years, 48.6% women, median follow-up period 8.3 years [Q1–Q3: 3.4–14.3]) and 73,080 from BWH (56.5±16.0, 54.7%, 7.5 [Q1–Q3: 3.0–12.6]). Across both institutions, there were a total of 12,168 AF events, 1,010 AF-related stroke events, and 2,935 AF-related HF events over the follow-up period ( Table 1 ). A higher ECG-AI risk score was independently associated with higher hazard for all outcomes ( Figure 1 ), and stratified the longitudinal risk of all outcomes ( Figure 2 ). For AF-related stroke, AUROC was 0.788 (95% confidence interval [CI] 0.743–0.835) at MGH and 0.815 (95% CI 0.791–0.843) at BWH. For AF-related HF, AUROC was 0.838 (95% CI 0.813–0.862) at MGH and 0.836 (95% CI 0.823–0.847) at BWH. Conclusion: An ECG-based AI model developed to predict incident AF also demonstrates potential to identify individuals at high risk of AF-related stroke and HF. Future work is warranted to investigate whether targeted preventive measures (e.g., AF screening) guided by ECG-based AI may reduce AF-related morbidity.

  PublisherDOI

• Artificial intelligence-enabled analysis of handheld single-lead electrocardiograms to predict incident atrial fibrillation: an analysis of the VITAL-AF randomized trial

  npj Digital Medicine · 2025-11-26 · 4 citations

  articleOpen access

  Whether artificial intelligence (AI) analysis of single-lead ECG (1 L ECG) can predict incident AF is unknown. In the VITAL-AF trial (ClinicalTrials.gov NCT03515057, registered 2/24/2021) of primary care patients aged ≥65 years undergoing handheld 1 L ECG screening, we tested three AI approaches to incident AF prediction, and compared the best model to the CHARGE-AF risk score. In a test set of 4,221 individuals, a published AI model trained using single standard ECG leads ("1 L ECG-AI") provided similar 2-year AF discrimination to models trained with VITAL-AF data. In the full VITAL-AF sample of 15,694 individuals without prevalent AF (2-year incident AF 3.1%), 1 L ECG-AI with age/sex (1 L ECG-AI AS) had comparable discrimination (area under the receiver operating characteristic curve [AUROC] 0.695[0.637-0.742]; average precision [AP] 0.060[0.050-0.078]) to CHARGE-AF (AUROC 0.679[0.623-0.730]; AP 0.062[0.052-0.080], AUROC p = 0.46, AP p = 0.92). Net reclassification improvement was favorable versus age ≥65 years (0.27[0.22-0.32]). 1 L ECG-AI may increase efficiency and reach of AF screening.

  PublisherOA PDFDOI

• U.S. public perceptions on whether risk of dementia and stroke can be modified through maintaining or changing lifestyle

  BMC Public Health · 2025-11-28

  articleOpen access

  BACKGROUND: Epidemiological studies suggest that approximately 40% of dementia and 60% of stroke cases could be prevented through adequate control of modifiable risk factors. Limited data are available on the public perceptions in the United States (U.S.) on whether the risk of dementia and stroke can be modified through lifestyle changes. METHODS: A survey utilizing questions from validated questionnaires was distributed to a sample of the general U.S. POPULATION: We performed multivariable logistic regression analyses for which the binary exposure was ever having known someone with dementia or stroke, and the primary outcomes were the perceptions on whether dementia and stroke risk could be modified through maintaining or changing lifestyle. RESULTS: We included 1,478 participants (mean [SD] age: 45.5 [15.9], 51.1% female), of whom 80% (N = 1185) ever knew someone with dementia or stroke. Over 75% of all participants perceived that a healthy lifestyle can lower dementia and stroke risks. Following multivariable analyses, participants who ever knew someone with dementia or stroke were more likely to agree that maintaining (adjusted Odds Ratio [aOR] = 1.41, 95%CI:1. 10-1.96) and that changing lifestyle (aOR = 1.59, 95%CI:1.14-2.24) reduces dementia risk, when adjusted for age, sex assigned at birth, race/ethnicity, level of education, employment status, and being a caregiver for someone with dementia or stroke. Participants who knew someone with dementia or stroke were also more likely to agree that maintaining (aOR = 1.77, 95%CI:1.27-2.47) or changing lifestyle (aOR = 2.31, 95%CI:1.41-3.76) reduces stroke risk when adjusted for similar confounders. DISCUSSION: This cross-sectional cohort, mimicking the general U.S. population, demonstrated that over 80% of individuals ever knew someone with dementia or stroke and that this was positively associated with the perceptions that dementia and stroke risk could be modified through lifestyle changes. The widespread exposure of the U.S. public to dementia and stroke first-hand can be leveraged into more effective preventive strategies.

  PublisherOA PDFDOI

• The Abbreviated Brain Care Score and Association With Incident Dementia, Stroke, and Late-Life Depression

  Neurology Open Access · 2025-11-12

  article
  PublisherDOI

Recent grants

• NIH Grant K23NS086873

  NIH · $951k · 2019

• ERICH-GENE

  NIH · $34.2M · 2010–2026

• NIH Grant R21DK090661

  NIH · $406k · 2014

• Sequencing Annotation and Functional Analysis in Risk of Intracerebral Hemorrhage

  NIH · $3.4M · 2018–2024

Frequent coauthors

• Jonathan Rosand

  Massachusetts General Hospital

  2109 shared

• Natalia S. Rost

  Massachusetts General Hospital

  1471 shared

• Hugh S. Markus

  University of Cambridge

  1405 shared

• Philip St. John

  University of Manitoba

  1344 shared

• Daniel Woo

  University of Cincinnati

  1233 shared

• Guido J. Falcone

  1126 shared

• Farid Radmanesh

  Brigham and Women's Hospital

  989 shared

• Martin Dichgans

  German Center for Neurodegenerative Diseases

  987 shared

Education

• MMSc

  Harvard Medical School

  2014

• MD

  Northwestern University Feinberg School of Medicine

  2005

• BA, Molecular and Cell Biology

  Northwestern University

  2001