Explore This Lab
Our group is headed by Dr. Joel Salinas, a behavioral neurologist and neuropsychiatrist with expertise in epidemiology and health outcomes research.
Our mission is to develop and deploy strategies that preserve brain health, restore brain function, and prevent brain disease across the lifespan.
The risk and course of age-related neurologic diseases, such as dementia and stroke, may be heavily influenced by a largely unexplained modifiable risk factor: social relationships.
Improved physical and mental health are closely associated with stronger social relationships, which encompass distinct functional (social support) and structural elements (social networks). Evidence implicating social isolation with higher risk of stroke, cognitive dysfunction, and accumulation of Alzheimer’s disease pathology suggests that a broader approach to potential therapeutic targets is necessary.
Since drug trials for Alzheimer’s disease and other causes of dementia remain largely unsuccessful, studying modifiable lifestyle factors such as social relationships for their impact on brain health could help us learn how to leverage them for prevention and therapy.
Because underlying molecular responses to genetic and environmental exposures begin early in disease development and regulation of gene expression is critical for these regulatory cellular mechanisms, the study of related molecular markers of subclinical neurodegeneration in parallel allows for a unique opportunity to identify neurobiological pathways for the social determinants of brain health.
Therefore, we use the intersection of biology and sociology to understand the mechanisms through which social relationships alter biology and harness what we learn to improve brain health for the population.
The first area of our research focuses on using outcomes research and mathematical network theory to identify the influence of a person’s social network and the support derived from their network as an independent predictor of brain health outcomes.
Questions that drive our research are: How do different forms of connectivity and proximity within a social network affect measures of subclinical neurodegeneration? What features within a network are most significant in reducing the risk of age-related brain disease and cognitive impairment? When reliably assessed over time, what changes in a social network confer the greatest effect on related health outcomes, such as quality of life, social participation, or the development of poststroke depression?
The second area of our work seeks to identify the underlying biological mechanisms through which social relationships influence brain health.
Human health and disease can be studied across a continuum of resolutions ranging from macroepidemiology to microepidemiology. Factors contributing to health and disease work within complex networks made up of a few “hubs” that are linked to many determinants and that are related in structure and function at the genetic, molecular, cellular, clinical, environmental, and societal levels.
Macroepidemiology lies on one end of the continuum with a focus on the individual’s environmental context, while microepidemiology, at the opposite end, focuses on the cellular and molecular context of the individual.
In its simplest form, the conceptual flow of relationships across all factors along the macro-micro continuum can be diagrammed as a cycle beginning at the level of the exposome—the collection of environmental, social, and behavioral determinants extending through influences on and from the genome, epigenome, transcriptome, proteome, metabolome, and metagenome—and manifesting through the collective milieu of the phenome, physiome, and diseasome.
Thus, the future of epidemiology will rely on using an integrated array of investigative lenses, or tool kits, that include the following:
- Combining individual and community approaches to studying health promotion and disease prevention (cHealth)
- Fully embedding social determinants of health into the biomedical model of disease (sHealth)
- Using advances derived from the digital revolution to better characterize the exposome (mHealth) with linkages to large electronic health datasets (eHealth)
- Channeling the momentum of the genomic and “biomarker” revolution toward enhancing precision medicine and personalized healthcare (gHealth and bHealth)
The capability to examine models of health and disease through each of these investigative lenses has the greatest potential for identifying insights into mechanisms and translating this knowledge into effective therapies via rapid iterations of validation and refinement.
To this end, we use large-scale longitudinal cohorts, including the Framingham Heart Study and the Women’s Health Initiative, to:
- Integrate microepidemiologic data (e.g., markers of gene expression, including non-coding RNA networks and proteomics) and macroepidemiology data (e.g., brain MRI measures and neuropsychological testing)
- Develop and validate emerging digital phenotyping tools and quantitative methods for measuring brain health and disease in real time
Visiting Scholar Program: We are enthusiastic about offering external scientists the opportunity to join us in our daily research work and exchange new ideas and perspectives.
We welcome individuals at different levels of clinical/academic training, with specific focus on providing students and trainees (undergraduate and graduate students, medical students, residents and fellows) with exposure to clinical research in the fields of neurology, psychiatry, epidemiology and biostatistics.
Each application is handled and considered individually. If interested, please contact us by email.
See the complete PubMed publication list.
Salinas J, Beiser A, Himali JJ, Satizabal CL, Aparicio HJ, Weinstein G, Mateen FJ, Berkman LF, Rosand J, Seshadri S. Associations between social relationship measures, serum brain-derived neurotrophic factor, and risk of stroke and dementia. (2017). Alzheimers Dement (N Y), 3(2), 229-237. doi: 10.1016/j.trci.2017.03.001.
Pubmed PMID: 29067329.
Salinas J, Ray RM, Nassir R, Lakshminarayan K, Dording C, Smoller J, Wassertheil-Smoller S, Rosand J, Dunn EC. Factors associated with new-onset depression following ischemic stroke: the Women’s Health Initiative. (2017). J Am Heart Assoc, 6(2), Epub 2017 Feb 6. doi: 10.1161/JAHA.116.003828.
Pubmed PMID: 28151400.
Wassertheil-Smoller S, Qi Q, Dave T, Mitchell BD, Jackson RD, Lius S, Park K, Salinas J, Dunn EC, Leira EC, Xu H, Ryan K, Smoller JW. Polygenic risk for depression increases risk of ischemic stroke: from the Stroke Genetics Network Study. (2018). Stroke, 49(3), 543-548. doi: 10.1161/STROKEAHA.117.018857.
Pubmed PMID: 29438084.