QUANTITATIVE METHODS TO MAP GENES FOR COMPLEX DISEASES Release Date: February 11, 1998 RFA: MH-98-017 P.T. National Institute of Mental Health National Human Genome Research Institute National Institute of General Medical Sciences National Institute of Neurological Disorders and Stroke National Institute of Dental Research National Institute of Diabetes and Digestive and Kidney Diseases National Institute on Aging National Institute of Environmental Health Sciences National Institute of Alcohol Abuse and Alcoholism National Eye Institute National Institute on Drug Abuse Letter of Intent Receipt Date: April 6, 1998 Application Receipt Date: May 6, 1998 PURPOSE The purpose of this Request for Applications (RFA) is to solicit applications for innovative research projects that will develop new quantitative methods for mapping sets of genes that influence susceptibility to complex human diseases. The specific objectives to be accomplished are: (1) the development of powerful and flexible statistical methods that will enable researchers to localize and map multiple disease susceptibility genes, and (2) the implementation of these new, sophisticated methods in highly efficient and well-documented computer programs widely disseminated for use by a broad range of biomedical researchers. Such methods will permit the rapid and efficient analysis of information derived from new maps of polymorphisms, in order to better correlate disease phenotypes with underlying genotypes. The widespread availability of innovative quantitative methods for genetic analysis will greatly foster gene discovery and stimulate many areas of biological research on complex diseases, particularly the ultimate identification of new treatments and preventive interventions. These new statistical tools are essential for obtaining the maximal yield of information from the avalanche of genomic information being generated from new and evolving molecular technologies. HEALTHY PEOPLE 2000 The Public Health Service (PHS) is committed to achieving the health promotion and disease prevention objectives of "Healthy People 2000," a PHS-led national activity for setting priority areas. This RFA, New Quantitative Methods to Map Genes for Complex Diseases, is related to many priority areas. Potential applicants may obtain a copy of "Healthy People 2000" (Full Report: Stock No. 017-001-00474-0 or Summary Report: Stock No. 017-001-00473-1) through the Superintendent of Documents, Government Printing Office, Washington, DC 20402-9325 (telephone 202-512-1800). ELIGIBILITY REQUIREMENTS Applications may be submitted by domestic and foreign, for-profit and non-profit organizations, public and private organizations, such as universities, colleges, hospitals, laboratories, units of State and local governments, and eligible agencies of the Federal Government. Racial/ethnic minority individuals, women, and persons with disabilities are encouraged to apply as principal investigators. MECHANISM OF SUPPORT All of the Institutes participating in this RFA will use the National Institutes of Health (NIH) individual research project grant (R01). The total project period for an application submitted in response to this RFA is not generally expected to exceed 3 years. Applicants requesting direct costs of $500,000 or more for any one year must obtain written agreement from National Institute of Mental Health (NIMH) staff that the application will be accepted for consideration of award, in accordance with NIH policy. The earliest anticipated award date is September 30, 1998. Responsibility for the planning, direction, and execution of the proposed project will be solely that of the applicant. Awards will be administered under PHS grants policy as stated in the PHS Grants Policy Statement. Future unsolicited competing continuation applications will compete with all investigator-initiated applications and will be reviewed according to the customary peer review procedures. For administrative reasons all applications received in response to this solicitation will be assigned initially to NIMH. After discussions among the participating Institutes and before review, applications will be reassigned to the Institute(s) that are programmatically most appropriate. Because the scope of the research proposed in response to this RFA encompasses the interests of several NIH Institutes, applications may receive dual assignments based on the established PHS guidelines. Awards will be made and managed by NIMH and/or the other participating Institutes. FUNDS AVAILABLE This RFA is a one-time solicitation. Approximately $4 million (including direct and indirect costs) per year will be available for this initiative. It is anticipated that 16 to 20 awards will be made. Awards pursuant to this RFA are contingent upon the availability of funds for this purpose. The amount of funding for these projects may be increased if a large number of highly meritorious applications are received and if funds are available. Only applications that are found to be of the highest scientific merit will be considered for funding and not all of the funding will be spent if there are not enough highly meritorious applications. Funding in future years will be subject to the availability of funds. RESEARCH OBJECTIVES Background Genetic factors contribute to virtually every human disease by conferring susceptibility or resistance, affecting the severity or progression of disease, and interacting with environmental factors that modify disease course and expression. Much of current biomedical research, in both the public and private sectors, is based upon the expectation that understanding the genetic basis of disease will revolutionize diagnosis, treatment, and prevention. Defining and understanding the role of genetic factors in disease will also allow the non- genetic, environmental contributions to disease to be more clearly identified and understood. Tremendous advances have occurred in mapping and cloning genes for diseases that follow Mendelian patterns in families. The three major analytic methods that have proved successful include: localization to a chromosomal region of several megabases by linkage analysis of family data, followed by fine genetic mapping, analysis of haplotypes for linkage disequilibrium mapping, and direct detection of an increased prevalence of a functional variant in affected individuals, through association analysis. These methods have led to the mapping of over 500 rare Mendelian diseases to specific chromosomal regions, with nearly 100 being cloned based on their position. Consequently, human genetics has sparked a revolution in medical science on the basis of this seemingly improbable notion that the systematic discovery of disease genes can occur without any prior biological clue as to how they function. These breakthroughs are steadily reshaping biological thinking and medical practice. In contrast, the discovery of genes that influence susceptibility to more common human diseases has proceeded slowly. The etiologies of these disorders are highly complex, with disease susceptibility likely influenced by multiple genes of small relative effect (frequently referred to as quantitative trait loci, or QTLs) and environmental factors. These complexities present a considerable challenge to geneticists, and account for the much more modest success of existing analytic methods in teasing apart multifactorial causes to dissect the genetic basis of common diseases. Traditional linkage analysis required specification of the mode of disease transmission. Denser maps led to methodologic improvements, by which several marker loci could be simultaneously analyzed to increase the information content of pedigree data. Given that the modes of transmission of common, complex diseases are unknown, there has been a recent focus on mode-of-inheritance-free linkage methods that use smaller subsets of family members (usually relative pairs). A powerful new approach for conducting nonparametric multipoint linkage analysis in moderately sized pedigrees has recently been implemented. Another new method for linkage analysis in nuclear families has been developed, which is parameterized in terms of the recurrence risks for different relative classes. Other newly developed variance component methods for analyzing extended pedigree data make no assumptions regarding the mode of inheritance, but make distributional assumptions and can be computationally intensive. Taken together, these new linkage methods offer significant computational and analytic advantages for the mapping of genes that underlie complex diseases: robustness to uncertainty about the mode of inheritance, given that specification of the mode of inheritance is not required, capacity for multipoint analysis, potentially involving dozens of markers, convenient computations in partially informative families, ability to infer missing parental genotypes, and the relatively low loss of power compared to parametric methods. However, limitations exist: the full information content of large extended pedigrees and of unaffected individuals cannot be taken into account, environmental or other factors that modify susceptibility to illness cannot be easily incorporated, locus heterogeneity cannot be specified, their robustness to violation of underlying assumptions is untested, or involvement of more than two disease loci cannot be explicitly modeled this is especially problematic, given that complex human diseases likely involve several genes in interaction. Association studies provide a complementary strategy for detection of complex disease susceptibility genes. Linkage disequilibrium, the nonrandom association of alleles at linked loci, occurs when haplotype combinations of alleles at different loci occur more frequently than would be expected by chance. Disequilibrium between closely linked loci will dissipate slowly over successive generations. Thus, it is hoped that detection of association between a marker and a disease will lead to the identification of a susceptibility locus near the marker. Fine-scale gene mapping by linkage disequilibrium works best with data from genetic isolates (e.g., North American Hutterites) because it is likely that there is only one or few ancestral haplotypes on which a disease mutation arose. A small founding population increases the likelihood that a disease mutation was introduced by a single individual, producing a strong association between the disease and a specific haplotype in the current generation. These methods were use to fine map disease genes for rare Mendelian disorders like diastrophic dysplasia, progressive myoclonus epilepsy, congenital nephrotic syndrome, and cartilage-hair hypoplasia. Recent extensions of linkage disequilibrium methods allow for consideration of multiple, multiallelic markers. However, limitations arise in the face of factors such as marker mutation, recurrent disease mutations, an unknown population growth rate, increased genetic drift, increased background kinship, reduced availability of kindreds, locus heterogeneity, and the involvement of multiple disease susceptibility loci. Another approach to association analysis is searching for an increased prevalence of a particular functional variant in affected individuals within coding regions of genes. In this fashion, a gene is directly implicated as influencing disease susceptibility. This is accomplished by searching for differences in the frequency of a marker allele between a sample of patients and controls. These two groups must be carefully matched for ethnicity or other factors that may contribute to genetic differences. Spurious association evidence can occur if the population from which these groups are drawn from is assumed to be homogeneous, but in fact is made up of different subpopulations with differing allele frequencies. Such population stratification is the major confounding factor in association studies and can be due to recent admixture of different populations or inappropriate matching of patients and controls. These problems are circumvented with family-based association designs, in which controls are constructed from the set of nontransmitted parental haplotypes. Large-scale testing by direct association analysis, even if one needs to test every human gene, offers a powerful methodology recently proposed as the method of choice for identifying the genes of modest effect that are likely operative in the transmission of complex diseases. Recent technological developments have enabled the identification of individual variations in DNA and a large increase in the number of available polymorphisms for use in genome-wide association studies to identify disease susceptibility genes. This approach should be particularly efficient for identifying genes with relatively common mutations that confer a modest or small effect on disease susceptibility. Simple, bi- allelic polymorphisms throughout the genome are being discovered, and systematic cataloging of this sequence variation will soon begin. Semi- or fully automated methods for the discovery and scoring of thousands of such single nucleotide polymorphisms (SNPs) currently under development will greatly facilitate disease gene detection through whole-genome association analysis. However, there are limitations in applying current direct association-based analytic approaches to search for genes that underlie complex diseases: the involvement of multiple susceptibility loci, potentially in interaction, cannot be modeled, information provided by environmental risk factors or other covariates that modulate disease susceptibility is not incorporated, and genetic heterogeneity cannot be modeled. Promising new methods and technologies are being developed to provide for rapid and efficient cataloging of human DNA sequence variation. The maximum yield from such discoveries will require more powerful and sophisticated quantitative methods of analysis. New methods are required to extract in a highly organized and efficient way the maximum yield of information from the avalanche of biological data to be generated, in order to: (1) localize and map genes of varying effect sizes, (2) better correlate the relationship between disease phenotype and underlying genotype, and (3) model highly complex modes of disease transmission. This RFA is intended to solicit applications that specifically address the development of highly practical and feasible quantitative analytic methods that can immediately be put into practice by a broad range of biomedical researchers in rapid and efficient genome-wide analyses. Objective and Scope Tremendous advances have been made in developing new statistical methods and computer software for quantitative genetic analysis. Current analytic methods have been successfully applied to map Mendelian disease genes, but are not well suited for the genetic analysis of complex human diseases. Human geneticists are now beginning to explore a new genetic frontier, driven by the inconvenient reality that most diseases of medical relevance have irregular familial patterns and lack a simple one-to-one correspondence between genotype and phenotype. The greatest challenge will be to produce innovative and novel analytic methods that can incorporate the full range of information being generated from new genetic and physical maps. Sophisticated quantitative methods for performing extensive multipoint analysis with large numbers of SNPs from a new genetic map of the human genome will greatly facilitate gene identification and elucidation of complex patterns of disease transmission. The inherent biologic complexity of complex diseases necessitates a critical need for new statistical tools for dissecting their genetic basis. As with any scientific endeavor, discoveries and insights into the biological underpinnings of complex diseases will only occur with the concomitant development of the tools and analytic methods adopted by its practitioners. The field of complex genetics is still at an early stage, but is ready to explode much as it has done with the analysis of rare Mendelian diseases. The primary goal of this RFA is to attract investigators from a variety of scientific disciplines with the promise of shedding new light on old problems, i.e., the spawning of novel and innovative statistical analytic techniques needed to provide the necessary methodologic scaffolding for significant biological discoveries in complex human diseases. This will be accomplished through solicitation of applications to develop innovative and powerful statistical methods for mapping complex disease susceptibility genes and understanding the mode of inheritance. These new, sophisticated methods will be made available to a broad range of biomedical researchers studying complex diseases, in the form of highly efficient, powerful, exportable, and well-documented computer programs released to the scientific community in a timely fashion. In order to achieve this goal, statistical geneticists are encouraged to collaborate with computer scientists in the development of software and thorough documentation that can be provided through a transparent graphical user interface. Applications are solicited to develop novel and creative quantitative methods that will facilitate: (1) discovery of genes, including estimation of their relative effect size, (2) analysis of large amounts of map and sequence data, to better correlate disease phenotypes with underlying genotypes, and (3) specification of complex modes of disease transmission, including the interplay of multiple genetic and environmental factors that act independently or interactively. It is expected that the methods to be developed will be implemented in rapid computational algorithms that will permit large-scale genomic analysis of sequence and map data. Areas of interest for new methodologic development include, but are not limited to, the following topics: o Resolution of locus or allelic heterogeneity, o Analysis of multiple disease loci that act independently or interactively, o Full extraction of information from multiple bi- or multiallelic markers, o Detection of disease susceptibility genes with a high population frequency, o Analysis of haplotype sharing across the genome, o Simultaneous consideration of multiple polymorphisms in a putative disease gene, o Rapid computation of multipoint likelihoods in extended pedigrees, o Rapid computations of identity-by-descent matrices in pedigrees with missing data, o Incorporation of information from multiple affected family members, o Incorporation of covariates (e.g., environmental risk factors, sex, age), o Gene-environment interaction, o Simultaneous analysis of information extracted from array technologies, o Integration of data from independent studies. The major focus is to develop robust and practical methods that can be applied by a broad range of biomedical scientists in data sets that currently exist, are being gathered, or will be gathered. The operating characteristics of the methods developed should be extensively explored through analysis of real or simulated data sets. If assumptions are made (e.g., regarding multivariate normality, mode of inheritance, population growth rate), it is expected that the robustness of the method will be examined in regard to violation of these assumptions. Special emphasis shall be placed on demonstrating the computational feasibility and robustness of the methods as applied in data sets of the size expected in practice. SPECIAL REQUIREMENTS Wide Distribution of Well-Documented Computer Programs It is expected that well-documented, efficient, and exportable computer programs will be developed to implement the new statistical genetic methods developed in projects funded under this RFA. The distribution of such well-documented software has been an essential element in the rapid progress made to map Mendelian disease genes. To address the joint interests of the government in the availability of, and access to, the results of publicly funded research and in the opportunity for economic development based on these results, NIH requires applicants who respond to this RFA to develop and propose specific plans for sharing the software generated through the grant. Applications submitted in response to this RFA must include a detailed plan and timetable for rapidly developing and widely distributing computer programs that implement the proposed methods to the scientific community of biomedical researchers studying the genetics of complex diseases. The preferred mode of distribution is through a well-publicized World Wide Web site. It is strongly encouraged that this site provides an opportunity for users to direct questions to the developer about the analytic methods and software. Successful applicants whose methods become widely distributed and utilized may apply in the future for funding to train users. The initial review group will comment on the proposed plan for making software and documentation widely available. The adequacy of the plan will also be considered by NIH staff as one of the criteria for award. The proposed sharing plan, after negotiation with the applicant when necessary, will be made a condition of the award. The evaluation of renewal applications will include an assessment of the effectiveness of software release, distribution, and documentation. LETTER OF INTENT Prospective applicants are encouraged to discuss their research objectives with NIMH staff early in their planning process. Prospective applicants are asked to submit, by April 6, 1998, a letter of intent that includes a descriptive title of the proposed research, the name, address, and telephone number of the principal investigator, the identities of other key personnel and participating institutions, and the number and title of the RFA in response to which the application may be submitted. Although a letter of intent is not required, is not binding, and does not enter into the review of a subsequent application, the information that it contains allows NIMH staff to estimate the potential review workload and avoid conflict of interest in the review. Any application that requests direct costs of $500,000 or more for any one year must follow the guidelines for acceptance for review provided in the NIH Guide for Grants and Contracts dated May 3, 1996. This may be accessed on the NIH Guide World Wide Web site at http://grants.nih.gov/grants/guide/notice-files/not96-117.html. The letter of intent is to be sent to: Dr. Steven O. Moldin Division of Basic and Clinical Neuroscience Research National Institute of Mental Health 5600 Fishers Lane, Room 10C-26 Rockville, MD 20857 Telephone: (301) 443-2037 FAX: (301) 443-9890 Email: smoldin@nih.gov APPLICATION PROCEDURES The research grant application form PHS 398 (rev. 5/95) is to be used in applying for these grants. These forms are available at most institutional offices of sponsored research and from the Division of Extramural Outreach and Information Resources, NIH, 6701 Rockledge Drive, MSC 7910, Bethesda, MD 20892-7910, telephone 301-710-0267, fax 301-480-0525, Email: asknih@od.nih.gov. The RFA label available in the PHS 398 (rev. 5/95) application form must be affixed to the bottom of the face page of the application. Failure to use this label could result in delayed processing of the application such that it may not reach the review committee in time for review. In addition, the RFA title and number, "New Quantitative Methods to Map Genes for Complex Diseases: MH-98-017", must be typed in section 2 of the face page of the application form and the YES box must be marked. Submit a signed, typewritten original of the application, including the checklist, and four photocopies, in one package to: CENTER FOR SCIENTIFIC REVIEW NATIONAL INSTITUTES OF HEALTH 6701 ROCKLEDGE DRIVE, ROOM 1040 - MSC 7710 BETHESDA, MD 20892-7710 BETHESDA, MD 20817 (for courier/express service) At the time of submission, one additional copy of the application must be sent to: Dr. Steven O. Moldin Division of Basic and Clinical Neuroscience Research National Institute of Mental Health 5600 Fishers Lane, Room 10C-26 Rockville, MD 20857 Applications must be received by May 6, 1998. If an application is received after that date, it will be returned to the applicant without review. The Center for Scientific Review (CSR) will not accept any application in response to this RFA that is essentially the same as one currently pending initial review, unless the applicant withdraws the pending application. CSR will not accept any application that is essentially the same as one already reviewed. This does not preclude the submission of substantial revisions of applications already reviewed, but such applications must include an introduction addressing the previous critique. REVIEW CONSIDERATIONS Upon receipt, applications will be reviewed for completeness by CSR and for responsiveness by NIMH staff. Incomplete applications will be returned to the applicant without further consideration. If the application is not responsive to the RFA, NIH staff will contact the applicant to determine whether to return the application to the applicant or submit it for review in competition with unsolicited applications at the next review cycle. Those applications that are complete and responsive to this RFA will be evaluated for scientific and technical merit in accordance with the criteria stated below by an appropriate peer review group. As part of the initial merit review, all applications will receive a written critique and may undergo a process in which only those applications deemed to have the highest scientific merit will be discussed and assigned a priority score. All applications will receive a second level of review by the appropriate National Advisory Council. Review Criteria o Significance: Does this study address the development of important quantitative methods for mapping genes for complex human diseases? If the specific aims of the application are achieved, how will this facilitate ultimate detection, isolation, and cloning of these genes? Do the new methods enhance understanding of modes of complex disease transmission, including the interplay of multiple genetic and environmental factors? What will be the effect of these methods on future genetic study designs, in which better correlations can be made between disease phenotype and genotype? o Approach: Are the conceptual framework, design, techniques, and approaches adequate, appropriate, and feasible to accomplish the specific aims of the project? Does the applicant acknowledge potential problem areas and consider alternate approaches? Is the scientific and technical merit of the proposed research sufficient to advance the objectives of the RFA? Can the methods be applied to the sample sizes expected in practice? o Innovation and originality: Does the project employ novel and creative concepts and approaches? Does the project challenge existing paradigms and foster new analytic approaches in developing computationally feasible methods? Are highly rapid computational algorithms employed? If the aims of the application are achieved, will the methods provide new analytic approaches to the discovery of genes that underlie complex diseases above and beyond what is currently available to the biomedical research community? o Investigator: Are the principal investigator and staff appropriately trained and well suited to carry out this work? Is the work proposed appropriate to the experience level of the principal investigator and other researchers (if any)? o Scalability: What is the likelihood that the methods will be rapidly available for efficient use by a broad range of biomedical investigators? o Integration with other resources: Are the plans adequate to integrate the methods with other mathematical (e.g., pedigree processing programs) and biological (e.g., SNPs) resources? o Exportability and accessibility: Will the methods developed in the research project be implemented in software that runs efficiently in a variety of computer environments and operating systems? Are the plans adequate for development of documentation? Will resulting computer programs be usable by, and accessible to, the broad scientific community of biomedical researchers studying the genetics of complex diseases? Will software and documentation be accessible via a transparent graphical user interface? o Environment: Does the scientific environment in which the work will be done contribute to the probability of success? Do the proposed methods take advantage of unique features of the scientific environment or employ useful collaborative arrangements? Is there evidence of institutional support? o Budget and duration: Are the proposed budget and duration appropriate in relation to the proposed research? The availability of special opportunities for furthering methods development through the use of unusual talent resources or environmental conditions in other countries which are not readily available in the United States, or which provide augmentation of existing U.S. resources, will be considered in the review. AWARD CRITERIA The earliest anticipated date of award is September 30, 1998. Subject to the availability of funds, and consonant with the priorities of this RFA, the participating Institutes will provides funds for a project period not generally expected to exceed 3-4 years. Factors that will be used to make award decisions are as follows: o Quality of the proposed project as determined by rigorous scientific peer review, o Cost effectiveness of the proposed strategy, o Promise of the proposed methods to accomplish the goals of this RFA, by facilitating the identification of genes that underlie complex human diseases and enhancing the understanding of the mode of complex disease inheritance, o Promise of the proposed methods to extend and improve upon pre-existing gene mapping methods, o Adequacy of plans to make exportable, rapid, and efficient computer programs and accompanying documentation that implement the methods developed as a result of this RFA highly accessible to the biomedical research community, o Availability of funds. INQUIRIES Written, telephone, and e-mail inquiries concerning this RFA are encouraged. The opportunity to clarify any issues or questions from potential applicants is welcome. Direct inquiries regarding programmatic issues to: Dr. Steven O. Moldin Division of Basic and Clinical Neuroscience Research National Institute of Mental Health 5600 Fishers Lane, Room 10C-26 Rockville, MD 20857 Telephone: 301-443-2037 FAX: 301-443-9890 E-mail: smoldin@nih.gov Programmatic contacts for the other participating Institutes are: Dr. Lisa D. Brooks Genetic Variation and Genome Informatics Programs National Human Genome Research Institute Building 38A, Room 614, MSC 6050 Bethesda, MD 20892-6050 Telephone: (301) 496-7531 FAX: (301) 480-2770 Email: lisa_brooks@nih.gov Dr. Irene Eckstrand Division of Genetics and Developmental Biology National Institute of General Medical Sciences Building 45, Room 2AS-25K, MSC 6200 Bethesda, MD 20892-6200 Telephone: (301) 594-0943 FAX: (301) 480-2228 Email: irene_eckstrand@nih.gov Dr. Joan Harmon Division of Diabetes, Endocrinology, and Metabolic Diseases National Institute of Diabetes and Digestive and Kidney Diseases Building 45, 5AN-18G, MSC 6600 Bethesda, MD 20892-6600 Telephone: (301) 594-8813 FAX: (301) 480-3503 Email: jh90u@nih.gov Dr. Linda A. Thomas Program Development Branch National Institute of Dental Research Building 45, Room 4AN-24J Bethesda, MD 20892 Telephone: (301) 594-2425 FAX: (301) 480-8318 Email: lt16r@nih.gov Dr. Robert W. Karp Division of Basic Research National Institute on Alcohol Abuse and Alcoholism 6000 Executive Boulevard, Suite 402, MSC 7003 Bethesda, MD 20892-7003 Telephone: (301) 443-4223 FAX: (301) 594-0673 Email: rkarp@willco.niaaa.nih.gov Dr. Maria Y. Giovanni Vision Research Program National Eye Institute Executive Plaza, Suite 350, MSC 7164 Bethesda, MD 20892-7164 Telephone: (301) 496-0484 FAX: (301) 402-0528 Email: myg@nei.nih.gov Dr. Harold Gordon Division of Clinical and Services Research National Institute on Drug Abuse 5600 Fishers Lane, Room 10A-46 Rockville, MD 20857 Telephone: (301) 443-4877 FAX: (301) 443-6814 Email: hg23r@nih.gov Dr. Jose Velazquez Division of Extramural Research and Training National Institute of Environmental Health Sciences P.O.Box 12233 Research Triangle Park, NC 27709 Telephone: (919) 541-4998 FAX: (919) 541-4937 Email: velazqu1@niehs.nih.gov Dr. Anna M. McCormick Biology of Aging Program National Institute on Aging 7201 Wisconsin Avenue, Suite 2C231 Bethesda, MD 20892-9205 Telephone: (301) 496-6402 FAX: (301) 492-0010 Email: am38k@nih.gov Dr. Judy A. Small Division of Fundamental Neuroscience and Developmental Disorders National Institute of Neurological Disorders and Stroke 7550 Wisconsin Avenue, Room 8C04 Bethesda, MD 20892-9170 Telephone: (301) 496-5821 FAX: (301) 402-0887 Email: js134h@nih.gov Direct inquiries regarding fiscal matters to: Ms. Diana S. Trunnell Grants Management Branch National Institute of Mental Health 5600 Fishers Lane, Room 7C-08 Rockville, MD 20857 Telephone: (301) 443-2805 FAX: (301) 443-6885 Email: Diana_Trunnell@nih.gov Fiscal and administrative contacts for the other participating Institutes are: Ms. Jean Cahill Grants Management Officer National Human Genome Research Institute Building 38A, Room 613, MSC 6050 Bethesda, MD 20892-6050 Telephone: (301) 402-0733 FAX: (301) 402-1951 Email: Jean_Cahill@nih.gov Mr. Gary Fleming Grants Management Branch National Institute on Drug Abuse 5600 Fishers Lane Rockville, MD 20857 Telephone: (301) 443-6710 FAX: (301) 594-6847 Email: gf6s@nih.gov Mr. David L. Mineo Grants Management Officer Division of Extramural Research and Training P.O. Box 12233 Research Triangle Park, NC 27709 Telephone: (919) 541-7628 FAX: (919) 541-2860 Email: mineo@niehs.nih.gov Ms. Nancy C. Dixon Division of Extramural Activities National Institute of Diabetes and Digestive and Kidney Diseases 45 Center Drive, MSC 6600 Bethesda, MD 20892-6600 Telephone: (301) 594-8854 FAX: (301) 480-4237 Email: dixonn@extra.niddk.nih.gov Mr. Martin R. Rubenstein Division of Extramural Research National Institute of Dental Research Building 45, Room 4AN43, MSC 6402 Bethesda, MD 20892-6402 Telephone: (301) 594-4800 FAX: (301) 480-8301 Email: Martin.Rubenstein@nih.gov Ms. Marcia Cohn Grants Management Officer National Institute of General Medical Sciences 45 Center Drive, Room 2AN-44E, MSC 6200 Bethesda, MD 20892-6200 Telephone: (301) 594-3918 FAX: (301) 480-2554 Email: cohnm@nigms.nih.gov Ms. Carolyn E. Grimes Grants Management Branch National Eye Institute Executive Plaza South, Suite 350, MSC 7164 Bethesda, MD 20892-7164 Telephone: (301) 496-5884 FAX: (301) 496-9997 Email: cegrimes@nei.nih.gov Ms. Linda Hilley Office of Planning and Resource Management National Institute on Alcohol Abuse and Alcoholism 6000 Executive Boulevard, Suite 504, MSC 7003 Bethesda, MD 20892-7003 Telephone: (301) 443-4703 FAX: (301) 443-3891 Email: lhilley@willco.niaaa.nih.gov Mr. Joseph Ellis Grants and Contracts Management Office National Institute on Aging 7201 Wisconsin Avenue, Suite 2C231 Bethesda, MD 20892-9205 Telephone: (301) 496-1472 FAX: (301) 402-0066 Email: ellisj@exmur.nia.nih.gov Ms. Tina Carlisle Grants Management Branch National Institute of Neurological Disorders and Stroke 7550 Wisconsin Avenue, Room 1004 Bethesda, MD 20892-9190 Telephone: (301) 496-9231 FAX: (301) 402-0218 Email: tc48k@nih.gov AUTHORITY AND REGULATIONS This program is described in the Catalog of Federal Domestic Assistance No. 93.242 (NIMH), 93.279 (NIDA), 93.172 (NHGRI), 93.114 (NIEHS), 93.273 (NIAAA), 93.121 (NIDR), 93.847 (NIDDK), 93.862 (NIGMS), 93.866 (NIA), 93.853 (NINDS), and 93.867 (NEI). Awards are made under authorization of the Public Health Service Act, Title IV, Part A (Public Law 78-410, as amended by Public Law 99-158, 42 USC 241 and 285) and administered under PHS grants policies and Federal Regulations 42 CFR 52 and 45 CFR Part 74. This program is not subject to the intergovernmental review requirements of Executive Order 12372 or Health Systems Agency review. Awards will be administered under PHS grants policy as stated in the Public Health Service Grants Policy Statement (April 1, 1994). PHS strongly encourages all grant and contract recipients to provide a smoke-free workplace and promote the nonuse of all tobacco products. In addition, Public Law 103-227, the Pro-Children Act of 1994, prohibits smoking in certain facilities (or in some cases, any portion of a facility) in which regular or routine education, library, day care, health care or early childhood development services are provided to children. This is consistent with the PHS mission to protect and advance the physical and mental health of the American people.

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