SBIR-STTR Award

The broad, long-term objective of the proposed research is to develop a software product that can be used to facilitate the analysis of genetic changes in order to elucidate chromosomal abnormalities that underlie diseases such as autism spectrum disorder, bipolar disorder, and schizophrenia. Recent technological advances allow samples of DNA from patients to be analyzed on single nucleotide polymorphism (SNP) arrays, generating up to millions of data points from each sample. These data must be analyzed to identify chromosomal abnormalities (e.g. DNA mutations, hemizygous or homozygous deletions, or translocations) that confer risk for these diseases. Two main approaches to data analysis include copy number estimates (based on the intensity of hybridization of samples to SNP arrays) and genotype analysis (revealing heterozygosity and homozygosity). Software such as Partek Genomics Suite (GS) exists to perform data analysis and visualization. A goal of this proposal is to add another dimension to the analysis of high density SNP data by incorporating information about the genetic relatedness of individuals into the data analysis repertoire of Partek GS. The specific aims are as follows. (1) Incorporate SNPtrio into a new Partek GS module. This program analyzes genotype and copy number data from trios consisting of father, mother, and child and produces graphical and tabular descriptions of uniparental inheritance (e.g. uniparental isodisomy in which two copies of a chromosome or chromosomal segment are inherited from one parent; such a mechanism is known to cause a variety of mental retardation and other syndromes). (2) Incorporate SNPduo into PartekGS; this program performs pairwise analyses of SNP data sets, allowing the description of relatedness between individuals (by identity-by-state measurements). This is useful for a variety of purposes including identifying outliers, replicate samples, non-paternity, and confirming the genetic relatedness of members of a pedigree. (3) Incorporate a set of analytic tools that measure meiotic recombination in pedigrees consisting of one, two, or three generations. Such tools may be useful to exclude loci in association studies or to characterize mechanisms by which deletions or duplications occur. The software tools described in aims (1) to (3) will be assembled into a new prototype version of Partek GS. In aim (4), this prototype will be used to analyze a set of 500,000 SNPs measured in 2,883 individuals from 700 families having two or more individuals affected with autism. This analysis will demonstrate the functionality of the Partek GS prototype, demonstrating the usefulness of incorporating new tools for genetic analysis to discover chromosomal abnormalities that may have roles in autism.

Public Health Relevance:
Newly available technologies allow the measurement of millions of variations in DNA sequence between samples from individuals with diseases (such as autism and schizophrenia) relative to unaffected individuals (controls). The proposed research is designed to create software analysis tools that will facilitate the discovery of chromosomal abnormalities in diseases. This may lead to treatments for these disorders, serving a large public health need.

Public Health Relevance Statement:
Project Narrative Newly available technologies allow the measurement of millions of variations in DNA sequence between samples from individuals with diseases (such as autism and schizophrenia) relative to unaffected individuals (controls). The proposed research is designed to create software analysis tools that will facilitate the discovery of chromosomal abnormalities in diseases. This may lead to treatments for these disorders, serving a large public health need.

Project Terms:
0-11 years old; 16p11.2; Aberrant Chromosome; Abnormalities, Chromosomal; Affect; Affective Psychosis, Bipolar; Alleles; Allelic Loss; Allelomorphs; Analysis, Data; Aneuploid; Aneuploidy; Au element; Autism; Autism, Early Infantile; Autism, Infantile; Autistic Disorder; Base Pairing; Bipolar Disorder; Child; Child Youth; Children (0-21); Chromosomal Aberrations; Chromosomal Alterations; Chromosomal Amplification; Chromosomal Duplication; Chromosome Aberrations; Chromosome Alterations; Chromosome Anomalies; Chromosome abnormality; Chromosomes; Complex; Computer Programs; Computer Software Tools; Computer software; Cytogenetic Aberrations; Cytogenetic Abnormalities; DNA; DNA Alteration; DNA Sequence; DNA mutation; Data; Data Analyses; Data Set; Dataset; Deoxyribonucleic Acid; Deposit; Deposition; Dimensions; Disease; Disorder; Event; Family; Fathers; GWAS; Gene Alteration; Gene Mutation; Generations; Genes; Genetic; Genetic Alteration; Genetic Change; Genetic analyses; Genetic defect; Genetic mutation; Genome; Genomics; Genotype; Goals; Gold; Hereditary; Human Genetics; Human, Child; Imagery; Individual; Inheritance Patterns; Inherited; Investigators; Kanner's Syndrome; Lead; Loss of Heterozygosity; Measurement; Measures; Meiosis; Meiotic Recombination; Mental Retardation; Mental disorders; Mental health disorders; Metric; Microarray Analysis; Microarray-Based Analysis; Missouri; Mothers; Mutation; NIMH; National Institute of Mental Health; National Institute of Mental Health (U.S.); On-Line Systems; Online Systems; Output; Parents; Patients; Pb element; Pedigree; Performance; Phase; Polymorphism, Single Base; Programs (PT); Programs [Publication Type]; Psychiatric Disease; Psychiatric Disorder; Psychosis, Manic-Depressive; Public Health; Relative; Relative (related person); Reporting; Research; Research Personnel; Researchers; Resolution; Role; SBIR; SBIRS (R43/44); SNP; SNPs; Sampling; Schizophrenia; Schizophrenic Disorders; Science of Statistics; Sequence Alteration; Series; Siblings; Single Nucleotide Polymorphism; Small Business Innovation Research; Small Business Innovation Research Grant; Software; Software Tools; Statistical Methods; Statistics; Syndrome; Technology; Testing; Tools, Software; Trisomy; Uniparental Disomy; United States National Institute of Mental Health; Unspecified Mental Disorder; Variant; Variation; Visualization; Work; autism spectrum disorder; base; bipolar affective disorder; children; computational tools; computer program/software; computerized tools; dementia praecox; density; design; designing; develop software; developing computer software; disease risk; disease/disorder; disorder risk; father role; genetic analysis; genetic pedigree; genetic resource; genome mutation; genome wide association scan; genome wide association studies; genome wide association study; genome-wide scan; genomewide association scan; genomewide association studies; genomewide association study; genomewide scan; grandchild; grandparent; heavy metal Pb; heavy metal lead; human disease; insight; manic depressive disorder; manic depressive illness; meiotic; member; mental illness; microarray technology; online computer; pedigree structure; programs; prototype; psychological disorder; public health medicine (field); public health relevance; role of father; schizophrenic; social role; software development; statistics; tool; web based; whole genome association studies; whole genome association study; youngster

The broad, long-term objective of the proposed research is to develop and market a commercial software product that can be used to facilitate the analysis of genetic changes in order to elucidate chromosomal abnormalities that underlie diseases such as autism spectrum disorder, bipolar disorder, and schizophrenia. Recent technological advances allow samples of DNA from patients to be analyzed on single nucleotide polymorphism (SNP) arrays, generating up to millions of data points from each sample. In parallel, next- generation sequencing (NGS) of whole genomes (or whole exomes) allows the determination of sequence data from individuals with mental health (or other) diseases, as well as sequence data from affected and unaffected family members. These data must be analyzed to identify chromosomal abnormalities (e.g. DNA mutations, hemizygous or homozygous deletions, or translocations) that confer risk for these diseases. Software such as Partek(R) Genomics Suite" (GS) offers a robust set of tools to perform data analysis and visualization. A goal of this proposal is to enhance the Partek GS and Partek Flow" commercial products by introducing innovative, practically useful software modules that define genetic relatedness in studies based on SNP and/or NGS data. Specific Aim 1 is to develop and incorporate methods for the determination of genetic relatedness based on SNP data (including data sets of pedigrees and large populations). These methods allow the relationship between all pairs of individuals in a data set to be determined with high accuracy (even for large studies with thousands of samples). Specific Aim 2 is to develop and incorporate methods for the determination of genetic relatedness based on NGS data, including whole genome sequences of individuals. These methods will provide a significant new dimension to the analysis of genome sequence data, facilitating the identification of variants that are relevant to disease. For Specific Aim 3 we will apply these novel methods to two data sets: whole exome sequence data from individuals with autism (data from over 800 trios obtained from dbGaP), and SNP and whole genome or whole exome sequences from quintets of father/mother/child1/child2/child3 in which at least one child is diagnosed with autism. These studies will demonstrate the utility of the novel software methods and demonstrate how they can facilitate the discovery of genetic variants that underlie autism and other mental health disorders.

Public Health Relevance Statement:


Public Health Relevance:
Newly available technologies allow the measurement of millions of variations in DNA sequence between samples from individuals with diseases (such as autism and schizophrenia) relative to unaffected individuals (controls). The proposed research is designed to create software analysis tools that will facilitate the discovery of chromosomal abnormalities in diseases. This may lead to improved diagnosis and treatments for these disorders, serving a large public health need.

Project Terms:
Affect; Algorithms; autism spectrum disorder; Autistic Disorder; base; Benchmarking; Biological Markers; Biomedical Research; Bipolar Disorder; Child; Chromosome abnormality; Clinical Research; Computer software; computerized tools; Data; Data Analyses; Data Set; database of Genotypes and Phenotypes; design; Diagnosis; Diagnostic; Dimensions; Disease; disorder risk; DNA; DNA Sequence; exome; exome sequencing; Family member; Fathers; Gene Mutation; Genes; Genetic; genetic analysis; genetic pedigree; genetic resource; genetic variant; Genome; genome sequencing; genome wide association study; Genomics; Genotype; Goals; grandchild; grandparent; Growth; Imagery; improved; Individual; innovation; interest; Lead; Maps; Marketing; Measurement; Measures; Meiotic Recombination; member; Mental disorders; Mental Health; Methods; Mothers; Mutation; Neurodevelopmental Disorder; next generation sequencing; novel; Parent-Child Relations; Parents; Patients; Performance; Phase; Population; Population Study; programs; public health medicine (field); public health relevance; Relative (related person); Reporting; Research; Research Project Grants; Sampling; Schizophrenia; Sensitivity and Specificity; Sequence Determination; Siblings; Single Nucleotide Polymorphism; Small Business Innovation Research Grant; Software Tools; Speed (motion); statistics; Technology; tool; Uniparental Disomy; Variant; Work