Familial Loading and Schizophrenia Risk Indicators

Schizophrenia is a severe mental illness, causing impairments in multiple psychosocial domains. Individuals with schizophrenia are often unable to maintain gainful employment to which private insurance is tied, and commonly must receive treatment in public-sector settings. For this reason, the mental health services at Grady Health System treat a disproportionately high number of individuals with schizophrenia compared to other local psychiatric services. The PI for this grant proposal is trained as a community psychiatrist and intends to focus his career on schizophrenia research in the public-sector setting. He is in his second year on faculty at Emory and is based full-time at Grady, where he sees both inpatients and outpatients with schizophrenia. This research project will extend and add to a study conducted by the PI over the past year, The ARIS Project (Associations among Risk Indicators in Schizophrenia). Five risk markers will be studied in patients with schizophrenia, their firstand second-degree relatives, and normal comparison participants: (1) impairments in olfactory identification (IOI), (2) impairments in working memory (IWM), (3) neurological soft signs (NSS), (4) minor physical anomalies (MPA), and (5) dermatoglyphic abnormalities (DA), which are subtle abnormalities of the fingerprint dermal ridge patterns. Like The ARIS Project, the project proposed herein will focus on these 5 risk markers, but it also will add two important and innovative facets to this line of research. First, patients and their relatives will be further classified based on a thorough assessment of family history, including an assessment of singleton (only one person in the family affected) versus multiplex (more than one person in the family affected) status. Thus, familial loading (or genetic load for the illness based on details of the family history) will be estimated for each patient and relative. Second, the project will also examine a specific genetic polymorphism that has received wide attention among schizophrenia researchers, but not in the context of these other risk indicators—the functional polymorphism in the catechol-Omethyltransferase (COMT) gene. This project will rely on data recently collected from 75 ARIS participants (requiring only a supplemental assessment from them) and will recruit an additional 125 participants for the full assessment. The project will seek to better understand the five risk indicators, especially in the context of familial loading, and will investigate associations between the risk indicators and the COMT polymorphism. The PI is interested in pursuing larger research projects on risk prediction and risk stratification for schizophrenia, and this project will collect important data for an R01 proposal. The PI’s mentor for this research is Dr. Elaine Walker. SPECIFIC AIMS AND HYPOTHESES Aim #1: To compare 5 subgroups on the 5 schizophrenia risk indicators of interest. Similar to the research on MPA by Griffiths et al. (1998), 5 subgroups will be studied: (1) patients with schizophrenia from multiplex families (Pt-Multi), (2) relatives of patients from multiplex families (Rel-Multi), (3) patients with schizophrenia from singleton families (Pt-Singl), (4) relatives of patients from singleton families (Rel-Singl), and (5) demographically-comparable normal comparison subjects with no evidence of psychotic illness in firstor second-degree relatives (Norm). These samples will be drawn from a low-income, predominantly African American, urban population, which is an advantage of this study design because of the lack of research in this population, despite the prominent burden of disease within it. • Hypothesis #1A: Three of the risk indicators (IOI, IWM, NSS) are predicted to be primarily markers of familial / genetic risk and will therefore show the following pattern: Pt-Multi/Rel-Multi > Pt-Singl/Rel-Singl > Norm. Emory Medical Care Foundation grant proposal 01 July 2005 Michael T. Compton, M.D., M.P.H. 2 That is, multiplex family members (patients and unaffected relatives) will have greater impairments in olfactory identification and working memory, compared to singleton family members (patients and unaffected relatives), who will in turn have greater impairments than normal controls. • Hypothesis #1B: Two of the risk indicators (MPA, DA) are predicted to be primarily markers of developmental / environmental insult and will therefore show the following pattern: Pt-Singl > Pt-Multi > Rel-Multi/Rel-Singl > Norm. That is, singleton patients will have more morphologic abnormalities than multiplex patients, and relatives of all patients will have fewer such abnormalities, though more than normal controls. Aim #2: To compare 5 subgroups on the prevalence of the COMT polymorphism, and to assess for associations between the polymorphism and the risk indicators. Drawing on the work of Goldberg et al. (2003), the ValMet functional polymorphism affects prefrontal function, and the high-activity Val allele may be a genetic risk factor for schizophrenia. This project will genotype participants at this polymorphism, to compare the patients and family members from singleton and multiplex families. Again, this project will benefit from the sample characteristics because most past research on the COMT polymorphism has been conducted in Caucasian samples only. • Hypothesis #2A: Patients and unaffected relatives from multiplex families will have a higher prevalence of the Val allele than singleton patients and unaffected relatives. • Hypothesis #2B: Val homozygotes will have more prominent IOI, as well as more prominent IWM, compared to Met carriers. Exploratory Aim: To assess the utility of a multivariate prediction model in determining subgroup membership based on the 5 risk indicators and the ValMet genotype. Discriminant function analysis or other modeling techniques will be used to determine the optimal set of predictors. Using the obtained discriminant functions, the sample can be reclassified to approximate the accuracy of prospective identification efforts based on the predictor variables (Carter et al., 2002). In such a model, specific interactions can be examined, including potential gene-environment interactions (e.g., COMT polymorphism x MPA, or familial load x DA).